CN107589420A - A kind of interior of articles component detection method, apparatus and system - Google Patents
A kind of interior of articles component detection method, apparatus and system Download PDFInfo
- Publication number
- CN107589420A CN107589420A CN201710800746.4A CN201710800746A CN107589420A CN 107589420 A CN107589420 A CN 107589420A CN 201710800746 A CN201710800746 A CN 201710800746A CN 107589420 A CN107589420 A CN 107589420A
- Authority
- CN
- China
- Prior art keywords
- under test
- object under
- internal structure
- interior
- medium
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Geophysics And Detection Of Objects (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a kind of interior of articles component detection method, apparatus and system, this method to include：Wave data is obtained, Wave data possesses signal data of the penetrability detectable signal after each dieletric reflection inside the object under test by detecting devices to what opaque object under test was launched；According to the Wave data, by signal inversion imaging, the internal structure cross-sectional image of the object under test is drawn；Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, the internal structure cross-sectional image is divided into multiple regions；The area ratio in each region and the internal structure cross-sectional image is calculated respectively, draws the composition accounting of each medium inside the object under test.The present invention, using signal inversion imaging, detects internal structure of body according to Wave data；By calculating the area ratio of each areas of dielectric and whole internal structure cross-sectional image, the composition accounting of each medium inside object under test is drawn.
Description
Technical field
The present invention relates to image processing techniques and signal processing technology field, more particularly to a kind of interior of articles component detection
Method, apparatus and system.
Background technology
At present, traditional object scanning scaling method can only scan the surface profile of object under test, i.e., sent out to object under test
The signal that ultrasonic wave, laser etc. do not have penetrability is penetrated, determines that the surface of object under test is taken turns according to the signal reflected to draw
It is wide.
And interior of articles often has complicated structure, and include many kinds of substance composition.It is single sometimes or under scene
The surface profile that single sweep obtains opaque object under test has been unable to meet demand, but needs complicated knot inside detecting object
Structure, distinguish, many kinds of substance composition of identification interior of articles, and the composition accounting of many kinds of substance composition.But prior art this
A part is almost blank, therefore how the material composition of detecting object internal structure and interior of articles is this area needs to solve
The problem of.
The content of the invention
It is an object of the invention to provide a kind of interior of articles component detection method, apparatus and system, to realize interior of articles
Component detection, the differentiation of each medium and the calculating of composition accounting.
To solve above-mentioned purpose, the present invention provides following technical scheme：
A kind of interior of articles component detection method, including：
Wave data is obtained, the Wave data possesses penetrability by detecting devices to what opaque object under test was launched
Signal data of the detectable signal after each dieletric reflection inside the object under test；
According to the Wave data, by signal inversion imaging, the internal structure cross-sectional image of the object under test is drawn；
Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, by the inside
Structure sectional view picture is divided into multiple regions；
The area ratio in each region and the internal structure cross-sectional image is calculated respectively, is drawn in the object under test
The composition accounting of each medium in portion.
Alternatively, it is described according to the Wave data, by signal inversion imaging, draw the inside structure of the object under test
Cross-sectional image is made, including：
According to two-dimensional radar Wave data, by radar signal inversion imaging, show that the two dimension of the object under test is internal
Structure sectional view picture；
Wherein, the two-dimensional radar Wave data is to detect the object under test simultaneously using more baseline linear distribution radars
The data of acquisition, or single base radar individually detect the data that the object under test obtains；
The process that single base radar individually detects the object under test is specially：
Single base radar positioned at default sampled point sends radar detection signal to the object under test, is treated described in reception
Survey the one-dimensional Wave data of each dieletric reflection in inside of object；
Based on the default sampled point, repeat to obtain the one-dimensional wave figurate number of multiple sampled points in the first preset direction
According to multiple one-dimensional Wave datas form two-dimensional radar waveform dataset.
Alternatively, the area ratio for calculating each region and the internal structure cross-sectional image respectively, draws institute
The composition accounting of each medium inside object under test is stated, including：
Each region in several described internal structure cross-sectional images and the internal structure sectional view are calculated respectively
The area ratio of picture；
According to multiple area ratios in the region corresponding to each medium, each region is calculated
Area is than average value, and using the composition accounting of the area than average value as the corresponding medium.
Alternatively, in the area ratio for calculating each region and the internal structure cross-sectional image respectively, draw
Inside the object under test after the composition accounting of each medium, in addition to：
Using the multiple two-dimentional internal structure cross-sectional images obtained on the second preset direction in pre-determined distance, form
The interior three-dimensional model of the object under test；
According to the interior three-dimensional model and area ratio, the volume of each medium is calculated；
Or
The three-dimensional radar Wave data that radar detects the object under test and obtain simultaneously is distributed according to using more base arrays,
By radar signal inversion imaging, the interior three-dimensional model of the object under test is drawn；
According to the interior three-dimensional model and area ratio, the volume of each medium is calculated.
Alternatively, it is described to utilize image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, with
The internal structure cross-sectional image is divided into multiple regions, including：
Using any of gray threshold segmentation algorithm, Region Segmentation Algorithm or rim detection partitioning algorithm, will belong to together
The same area is divided in a kind of pixel of medium, the internal structure cross-sectional image is divided into multiple regions.
Alternatively, inverting is carried out to the Wave data, draws the object under test by signal inversion imaging described
Internal structure cross-sectional image after, using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to same area
Domain, before the internal structure cross-sectional image is divided into multiple regions, in addition to：
Image pretreatment operation is carried out to the internal structure cross-sectional image；
Wherein, described image pretreatment operation comprise at least Slant Rectify, cut, denoising, enhancing and rasterizing.
A kind of interior of articles component detecting device, including：
Acquisition module, for obtaining Wave data, the Wave data is sent out by detecting devices to opaque object under test
That penetrates possesses signal data of the penetrability detectable signal after each dieletric reflection inside the object under test；
Inversion imaging module, for according to the Wave data, by signal inversion imaging, drawing the object under test
Internal structure cross-sectional image；
Image segmentation module, for using image segmentation algorithm, will belong to a kind of pixel of medium be divided to it is same
Region, the internal structure cross-sectional image is divided into multiple regions；
Medium accounting computing module, for calculating the area in each region and the internal structure cross-sectional image respectively
Than drawing the composition accounting of each medium inside the object under test.
Alternatively, the inversion imaging module includes：
Radar inversion imaging submodule, for according to two-dimensional radar Wave data, by radar signal inversion imaging, drawing
The two-dimentional internal structure cross-sectional image of the object under test；
Wherein, the two-dimensional radar Wave data is to detect the object under test simultaneously using more baseline linear distribution radars
The data of acquisition, or single base radar individually detect the data that the object under test obtains；
The process that single base radar individually detects the object under test is specially：
Single base radar positioned at default sampled point sends radar detection signal to the object under test, is treated described in reception
Survey the one-dimensional Wave data of radar detection signal described in each dieletric reflection in inside of object；
Based on the default sampled point, repeat to obtain the one-dimensional wave figurate number of multiple sampled points in the first preset direction
According to multiple one-dimensional Wave datas form two-dimensional radar waveform dataset.
Alternatively, the medium accounting computing module includes：
Area is than calculating sub module, for calculating each region in several described internal structure cross-sectional images respectively
With the area ratio of the internal structure cross-sectional image；
Mean value calculation submodule, for multiple area ratios in the region according to corresponding to each medium,
The area in each region is calculated than average value, and using the area than average value as described in the corresponding medium
Composition accounting.
Alternatively, in addition to：
Interior three-dimensional model construction module, for multiple described using what is obtained on the second preset direction in pre-determined distance
Two-dimentional internal structure cross-sectional image, form the interior three-dimensional model of the object under test；Or
Interior three-dimensional model inverter module, for detecting the determinand simultaneously according to using more base arrays distribution radar
The three-dimensional radar Wave data that body obtains, by radar signal inversion imaging, draw the interior three-dimensional model of the object under test；
Medium volume computing module, for according to the interior three-dimensional model and area ratio, each institute to be calculated
Give an account of the volume of matter.
Alternatively, described image segmentation module includes：
Split submodule, for using in gray threshold segmentation algorithm, Region Segmentation Algorithm or rim detection partitioning algorithm
It is any, a kind of pixel of medium will be belonged to and be divided to the same area, by the internal structure cross-sectional image split
Into multiple regions.
Alternatively, in addition to：
Image pre-processing module, for carrying out image pretreatment operation to the internal structure cross-sectional image；
Wherein, described image pretreatment operation comprise at least Slant Rectify, cut, denoising, enhancing and rasterizing.
A kind of interior of articles component detection system, including detecting devices and processing terminal；
The detecting devices is used for the detectable signal for possessing penetrability to the transmitting of opaque object under test and receives the spy
Wave data of the signal through each dieletric reflection inside the object under test is surveyed, and the Wave data is sent to the processing eventually
End；
The processing terminal is used to receive the Wave data；According to the Wave data, by signal inversion imaging, obtain
Go out the internal structure cross-sectional image of the object under test；Using image segmentation algorithm, a kind of pixel dot-dash of medium will be belonged to
Divide to the same area, the internal structure cross-sectional image is divided into multiple regions；Each region and institute are calculated respectively
The area ratio of internal structure cross-sectional image is stated, draws the composition accounting of each medium inside the object under test.
Alternatively, the processing terminal is additionally operable to the composition accounting according to each medium, calculates the determinand
The volume of each medium in internal portion.
Alternatively, the detecting devices is GPR, and the detectable signal is high frequency electromagnetic wave signal.
Interior of articles component detection method provided by the present invention, this method are by obtaining Wave data, Wave data
Detecting devices possesses penetrability detectable signal by each medium inside the object under test to what opaque object under test was launched
Signal data after reflection；According to the Wave data, by signal inversion imaging, the internal structure of the object under test is drawn
Cross-sectional image；Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, by the inside
Structure sectional view picture is divided into multiple regions；The area in each region and the internal structure cross-sectional image is calculated respectively
Than drawing the composition accounting of each medium inside the object under test.
It can be seen that Wave data is carried out inverting by this method using signal inverting, the internal structure section of object under test is drawn
Image, so as to detect the internal structure of object under test；Split using image internal structure cross-sectional image is divided into it is multiple
Region, the pixel in each region belong to a kind of medium, that is, have distinguished each medium inside object under test；Pass through meter
The area ratio that each areas of dielectric accounts for whole internal structure cross-sectional image is calculated, has been drawn inside object under test shared by each medium
Ratio.Interior of articles component detecting device provided by the present invention is same with interior of articles component detection system with above-mentioned beneficial
Effect.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
The embodiment of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
Fig. 1 is that a kind of flow of embodiment of interior of articles component detection method provided in an embodiment of the present invention is shown
It is intended to；
Fig. 2 is that detectable signal provided in an embodiment of the present invention feedback waveform changes over time figure；
Fig. 3 is a kind of one-dimensional oscillogram provided in an embodiment of the present invention；
Fig. 4 is the dimensional waveform image that multiple one-dimensional waveforms provided in an embodiment of the present invention are combined into；
Fig. 5 is the gray scale inner section image that inverting provided in an embodiment of the present invention is drawn；
Fig. 6 is object under test medium volume calculation process schematic diagram provided in an embodiment of the present invention；
Fig. 7 is the structural schematic block diagram of interior of articles component detecting device provided in an embodiment of the present invention；
Fig. 8 is the structural schematic block diagram of interior of articles component detection system provided in an embodiment of the present invention.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
Part of the embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
Embodiment one
Fig. 1 is refer to, Fig. 1 is a kind of specific embodiment party of interior of articles component detection method provided in an embodiment of the present invention
The schematic flow sheet of formula, this method may comprise steps of：
Step 101：Wave data is obtained, Wave data is worn by detecting devices to possessing of launching of opaque object under test
Signal data of the permeability detectable signal after each dieletric reflection inside object under test.
It is to be appreciated that mutation, damage will not occur because of detectable signal and other irreversible change for the internal structure of object under test
Become.During detectable signal reflects from injection object under test to object under test, signal intensity attenuation can be ignored.
And a variety of media inside object under test have differences in physical characteristic, i.e., each material corresponds to a kind of transmission medium,
When detectable signal transmits in different material, the parameter such as possessed waveform is different；That is, detectable signal passes through determinand
The signal that a variety of dieletric reflections in internal portion are returned be it is different, can be according to the difference of the signal reflected, so as to distinguish
The various materials of interior of articles.
Detecting devices can be specially GPR, or it is other possess transmitting and receive penetrate setting for signal capabilities
It is standby；Correspondingly, detectable signal can be specially high frequency electromagnetic wave signal, or other signals for possessing identity function,
This is not construed as limiting.
Above-mentioned Wave data is detectable signal through the signal data that each dieletric reflection is returned inside object under test, detection letter
Number penetrability detectable signal launched in certain sampled point to object under test for detecting devices.Detecting devices, which receives, to be reflected
Feedback oscillogram after, feedback oscillogram, the related data such as sampling point information are sent to data processing terminal in the lump, so that number
Data processing is carried out according to processing terminal.
Step 102：According to Wave data, by signal inversion imaging, the internal structure cross-sectional image of object under test is drawn.
It is appreciated that received Wave data can be one-dimensional Wave data or dimensional waveform data or
Three-dimensional waveform data.And the difference of detecting devices, the classification of Wave data also can be accordingly different.
In some embodiments, detecting devices can be specially GPR, now, above-mentioned according to waveform number
According to by signal inversion imaging, drawing the process of the internal structure cross-sectional image of object under test can be specially：According to two-dimentional thunder
Up to Wave data, by radar signal inversion imaging, the two-dimentional internal structure cross-sectional image of object under test is drawn；
Wherein, two-dimensional radar Wave data is the number for detecting object under test acquisition simultaneously using more baseline linear distribution radars
According to, or single base radar individually detect object under test acquisition data；The process that single base radar individually detects object under test is specially：
Single base radar positioned at default sampled point sends radar detection signal to object under test, receives each medium in inside of object under test
The one-dimensional Wave data of reflection；Based on default sampled point, the one-dimensional Wave data of multiple sampled points is obtained in the first preset direction,
Multiple one-dimensional Wave datas form two-dimensional radar waveform dataset.
It is to be appreciated that internal structure cross-sectional image is two dimensional image, the image can utilize radar signal inversion imaging skill
Art, signal inverting is carried out based on two-dimensional radar oscillogram and drawn.And the two-dimensional radar oscillogram can be visited by single GPR
Survey object under test to draw, object under test can also be detected simultaneously by multiple GPRs and drawn.
When detecting object under test simultaneously using multiple GPRs, this multiple GPR is in more baseline linear distributions,
I.e. multiple radars can form a radar array, and the array can be M*1 or 1*N, that is, multiple radars can be along some direction
Linear distribution, and should be at a distance of suitable distance between each radar.For example, M GPR is arranged along X-axis or Y-axis, M spy
Ground radar detects object under test simultaneously, you can obtains interior of articles dimensional waveform data set.
When using single ground penetrating radar detection object, first, the detectable signal of detection radar is injected from default sampled point
Object under test, detection radar receive the one-dimensional oscillogram reflected, obtain the one-dimensional Wave data of the sampled point.The one-dimensional wave
The unique variable of graphic data is the time (or penetrating depth), then the mathematic(al) representation of the one-dimensional waveform can be specially：
Wave=A (xi,yi,t)
F (z)=u (xi,yi,zk)zk∝t
Wherein, (xi,yi) be sampled point coordinate, i, j are constant, and k is variable；zkFor penetrating depth, it is with the time into just
The relation of ratio.
Preferably to introduce one-dimensional Wave data figure, Fig. 2 and Fig. 3 are referred to, Fig. 2 is detection provided in an embodiment of the present invention
Signal feedback waveform changes over time figure, and Fig. 3 is a kind of one-dimensional oscillogram provided in an embodiment of the present invention.
After the one-dimensional Wave data for obtaining a sampled point, multiple sampled points are taken along the first preset direction, successively more than this
Individual sampled point is acquired, and obtains this multiple sampled point one-dimensional Wave data figure accordingly respectively.And this first preset direction can
Be arbitrarily, its can be along x-axis, can also be along y-axis, also either other fixed-directions.
And in practical operation, the antenna of detecting devices can be moved along some fixed-direction, repetition obtains each
The one-dimensional Wave data figure of sampled point.After the corresponding one-dimensional Wave data figure for obtaining multiple sampled points of some fixed-direction,
This multiple one-dimensional Wave data figure is combined along moving direction, may be constructed a dimensional waveform diagram data collection.And work as along x
When axle moves, the mathematic(al) representation of this dimensional waveform data set can be with as follows：
Wave=A (x, yi,t)
F (z)=u (x, yi,zk)
Now, the variable in wave function has x and t.Certainly, sampled point along y-axis be distributed when, its variable also can mutually should be y
And t.
Herein, the position of sampled point can be specifically arranged at directly over object under test surface or object under test
On datum plane.And the interval between this multiple sampled point should be reasonable, not influence the one-dimensional wave figurate number that each sampled point is obtained
According to being defined.
Preferably to introduce the dimensional waveform data that multiple one-dimensional Wave datas are combined into, enter below in conjunction with Fig. 4
Row is introduced, and Fig. 4 is the dimensional waveform image that multiple one-dimensional waveforms provided in an embodiment of the present invention are combined into.As shown in figure 4, x-axis
For the linear moving direction of exploring antenna, one-dimensional oscillogram corresponding to multiple sampled points along x-axis distribution is combined, then may be used
To draw dimensional waveform datagram.
After obtaining dimensional waveform figure, the method for radar signal inversion imaging can be utilized, you can obtain interior of articles construction
Cross-sectional image.And radar signal inversion imaging technology is more ripe technology, it has been well known to those skilled in the art, herein not
Repeat again.
To make interior of articles structure sectional view picture more visual and understandable, the gray scale that the inverting shown in Fig. 5 is drawn for details, reference can be made to
Inner section image.Fig. 5 includes three width figures, is real-world object internal model, radar signal figure and inverting successively from left to right
The gray scale inner section image drawn.
Step 103：Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, will
Internal structure cross-sectional image is divided into multiple regions.
It is appreciated that after obtaining internal structure cross-sectional image using signal inverting, split for ease of successive image, in signal
After inversion imaging, before image segmentation, the internal structure cross-sectional image that can be drawn to signal inverting carries out image preprocessing.
In some embodiments, by signal inversion imaging, inverting is carried out to Wave data, draws determinand
After the internal structure cross-sectional image of body, using image segmentation algorithm, will belong to a kind of pixel of medium be divided to it is same
Region, before the internal structure cross-sectional image is divided into multiple regions, it can also include：To internal structure cross-sectional image
Carry out image pretreatment operation；Wherein, image pretreatment operation comprise at least Slant Rectify, cut, denoising, enhancing and grid
Change.
Because the incident angle by detectable signal, coordinate reference system are influenceed the problems such as selection, in the two dimension obtained
Cage structure cross-sectional image is probably inclined.For ease of the subsequent analysis of image, two dimensional gray cross-sectional image can be inclined
Tiltedly correction.Specifically, two dimensional gray cross-sectional image can be rotated to an angle, makes it (to pre-set in the frame of reference
, not by the standard square coordinate system of external interference) in be horizontally parallel to x-axis presentation.
And when measuring targets carry out internal component detection, the presence of the non-object under test on object under test periphery also can be right
The two-dimentional internal structure cross-sectional image obtained has an impact.Image after Slant Rectify needs to delimit the side of analysis sample
Boundary, and being cut according to this border to the image after correction, only the internal component to the object under test in border be measured,
Identification.Image, which is cut, can exclude the influence that non-object under test is brought.
Can successfully to be detected, the feedback signal of detecting devices must obtain sufficiently high signal to noise ratio, enough
Azimuth discrimination degree and depth resolution.And during actual detection, non-targeted clutter noise caused by extraneous and internal factor
It is unavoidable.Wherein, the noise in two dimensional gray cross-sectional image is mainly by unrelated with target scattering characteristics to be measured, but with
Target wavelet to be measured is appeared in same sampling time window, and has the noise signal of similar spectral characteristic to target wavelet to be measured
Composition.Specifically, averaging method can be used to remove two dimensional gray cross-sectional image background, to reject most of Land-oceanic clutters.
Further, it is also possible to the signal enhancing means using clutters such as other enhancing target echoes, suppression Land-oceanic clutters.And
Two-dimentional internal structure cross-sectional image can be carried out to pixelation, rasterizing processing, and cross-sectional image progress gray scale is become more meticulous place
Reason.
Certainly, except above-mentioned image pretreatment operation, other pretreatment operations can also be increased according to the actual requirements.
After image preprocessing, image segmentation algorithm can be used, internal structure cross-sectional image is divided into multiple figures
As region, the pixel included in each region belongs to a kind of medium.That is image segmentation can will belong to a kind of Jie
Part is referred to together corresponding to matter composition, to distinguish different medium composition.For example, when having n kind media inside actual object,
The region that image segmentation is drawn also should be n region.
Image segmentation algorithm can be selected according to the actual requirements, be specifically as follows but be not limited to gray level threshold segmentation calculation
Any of method, Region Segmentation Algorithm and rim detection partitioning algorithm.Therefore in some embodiments, this step can be with
For example,：Using any of gray threshold segmentation algorithm, Region Segmentation Algorithm or rim detection partitioning algorithm, will belong to
A kind of pixel of medium is divided to the same area, and internal structure cross-sectional image is divided into multiple regions.
Wherein, gray threshold segmentation algorithm can be based on gray difference and different types of interior media composition is carried out into area
Point, i.e., handled by image gray processing, the waveform that variety classes medium composition reflects is corresponded to the gray scale of different stage.Root
According to the gray difference between different types of medium composition and background, background area and target area are made a distinction, the target area
Domain is the region for including different types of medium composition inside object under test, and target area has different grey-scale other.Typically
Ground, gray threshold segmentation algorithm can be specially maximum variance between clusters.
Segmentation based on the threshold method of the gray difference scenery stronger to object and background contrast has obvious advantage.Can
To be preferentially used for handling on cross-sectional image, gray difference is larger and the nonoverlapping region in border.But if inside object under test
Complicated component and more approximate, gray threshold segmentation algorithm is then difficult to meet demand.
The space local feature that Region Segmentation Algorithm may rely on cross-sectional image carries out image segmentation.Gray scale, texture and
Uniformity of other pixels statisticses characteristics etc. could act as image characteristics extraction and as the foundation of image division.Drawn according to feature
The method of partial image has stronger noise immunity to the noise in image.In general, will be full in image using region-growing method
The pixel of certain similarity criterion of foot, which gathers, forms region.One nascent " seed point " is chosen first, foundation gray scale,
The parameter such as pixel distribution situation, gradient or geometric properties in region, the region for meeting specific region uniformity is incorporated into together,
Pixel cell without uniformity is separated.
Rim detection partitioning algorithm can realize that image is split by the edge of different zones in detection image.It can example
Such as it is method of differential operator, Model match method, Wavelet Detection method and neural network.Herein, method of differential operator can be used, its
Mainly with the operator detection method such as Roberts, Sobel, Prewitt, Canny and Second order directional.
Step 104：The area ratio of regional and internal structure cross-sectional image is calculated respectively, is drawn each inside object under test
The composition accounting of individual medium.
It is appreciated that by calculating total pixel of each image-region and total pixel of view picture internal structure cross-sectional image
The number ratio of point, then can show that each region accounts for the area ratio of internal structure cross-sectional image.The area ratio in each region can
Medium shared composition in object under test is corresponded to characterize the region.
The medium composition accounting that area in a certain width internal structure cross-sectional image can be used for inside object under test,
But because each section of object under test is different from, i.e., in the cross-sectional image of each position of object under test, Ge Gejie
The composition accounting of matter is probably unequal.Therefore in order to improve the accuracy rate of calculated medium composition accounting, then it can use
Repeatedly calculate the mode being averaged.
Therefore in some embodiments, this step can be, for example, specifically：Several internal structure sections are calculated respectively
The area ratio of regional and internal structure cross-sectional image in image；According to multiple areas in region corresponding to each medium
Than, the area in each region is calculated than average value, and using composition accounting of the area than average value as respective media.
It is to be appreciated that several above-mentioned internal structure cross-sectional images can be multiple sampling locations near each sampled point
Using the image of acquisition, and the interval between this multiple sampling location should not be interfere with each other by the radar of two positions and is defined.
The area ratio of the regional in every width internal structure cross-sectional image is calculated respectively, and so each areas of dielectric has
Multiple area ratios, calculate this multiple area than average value, the composition accounting using the average value as respective media.
As can be seen that the area for calculating several inner section structural map pictures can improve Jie being calculated than average value
The accuracy rate of matter composition accounting.
In the present embodiment, according to the Wave data gathered, using signal inversion imaging, the inside of object under test has been drawn
Structure sectional view picture, so as to detect the internal structure of object under test；Internal structure cross-sectional image is divided using image segmentation
It is cut into multiple regions, the pixel in each region belongs to a kind of medium, that is, has distinguished each Jie inside object under test
Matter；The area ratio of whole internal structure cross-sectional image is accounted for by calculating each areas of dielectric, has been drawn each inside object under test
Ratio shared by medium.
Embodiment two
The composition accounting of every kind of medium inside object under test is calculated, namely determines and is gathered in the range of pre-set space
Several internal structure cross-sectional images in various medium compositions content.So, this several internal structure cross-sectional image can be with structure
Into the interior of articles threedimensional model of object under test, the volume of various media in object under test can be then calculated.
After the present embodiment will be to calculating composition accounting, the volume for how calculating various media is introduced.Refer to
Fig. 6, Fig. 6 are object under test medium volume calculation process schematic diagram provided in an embodiment of the present invention.
Based on above-described embodiment one, the area ratio of regional and internal structure cross-sectional image is being calculated respectively, is drawing and treats
Survey after the composition accounting of each medium of interior of articles, can also comprise the following steps：
Step 601：Using the multiple two-dimentional internal structure cross-sectional images obtained on the second preset direction in pre-determined distance,
Form the interior three-dimensional model of object under test.
Multiple two-dimentional internal structure cross-sectional images may be constructed the interior three-dimensional model of object, that is to say, that a two dimension
Gray scale cross-sectional image after producing certain displacement, then can draw the object for describing object under test according to some fixed-direction
Interior three-dimensional model.
Step 602：According to interior three-dimensional model and area ratio, the volume of each medium is calculated.
In shift length, the region of each medium composition in two dimensional gray cross-sectional image and occupied area are than keeping one
Cause, i.e., in shift length, the region of each medium composition is not mutated between adjacent sections inside object under test.It is based on
This, shift length is multiplied by by the area of each medium, then can draw volume of each medium composition in the range of pre-set space.
In addition, interior of articles threedimensional model can also carry out signal inversion imaging directly according to three-dimensional waveform data
Draw.Then each medium is calculated in certain space scope based on interior three-dimensional model and the area ratio calculated again
Interior volume.
In some embodiments, the area ratio of regional and internal structure cross-sectional image is being calculated respectively, obtaining
Go out after the composition accounting of each medium in object under test inside, can also include：According to same using more base arrays distribution radar
When detect the three-dimensional radar Wave data that object under test obtains, by radar signal inversion imaging, draw the inside of object under test
Threedimensional model；According to interior three-dimensional model and area ratio, the volume of each medium is calculated.
It is to be appreciated that multiple radars that three-dimensional radar Wave data can be distributed by more base arrays detect determinand simultaneously
Body show that the radar array of this multiple radar composition is specially M*N；Can also be by multiple radar detections of more base linear distributions
Object under test show that the radar array formed is M*1 or 1*N, for example, when object under test is road surface, using one group in straight
Single base radar of line arrangement forms single radar group, and one group of sampling can obtain the gray scale in a section below sampling location simultaneously
Image, sampling obtains the gray-scale map in another section below sampling location again after the single radar group is moved a certain distance
Picture, the like, then sample once at a certain distance, the three-dimensional of road surface within the specific limits can be then obtained after multiple repairing weld
Three-dimensional model.Certainly, three-dimensional radar Wave data can also be drawn by single radar detection.
After the interior three-dimensional model for obtaining object under test, the area calculated is multiplied by certain distance, then can be drawn each
The volume in the range of certain space of individual medium.
In the present embodiment, according to the composition accounting of each medium, the volume of each medium in object under test is extrapolated.
Embodiment three
Interior of articles component detecting device provided in an embodiment of the present invention is introduced below, in object described below
Portion's component detecting device can be mutually to should refer to above-described interior of articles component detection method.
Fig. 7 is refer to, Fig. 7 is the structural schematic block diagram of interior of articles component detecting device provided in an embodiment of the present invention,
The device can include：
Acquisition module 71, for obtaining Wave data, Wave data is launched by detecting devices to opaque object under test
Possess signal data of the penetrability detectable signal inside the object under test after each dieletric reflection；
Inversion imaging module 72, for according to Wave data, by signal inversion imaging, draw the inside structure of object under test
Make cross-sectional image；
Image segmentation module 73, for using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to together
One region, internal structure cross-sectional image is divided into multiple regions；
Medium accounting computing module 74, for calculating the area ratio of regional and internal structure cross-sectional image respectively, obtain
Go out the composition accounting of each medium inside object under test.
In some embodiments, inversion imaging module can include：
Radar inversion imaging submodule, for according to two-dimensional radar Wave data, by radar signal inversion imaging, drawing
The two-dimentional internal structure cross-sectional image of object under test；
Wherein, two-dimensional radar Wave data is the number for detecting object under test acquisition simultaneously using more baseline linear distribution radars
According to, or single base radar individually detect object under test acquisition data；
The process that single base radar individually detects object under test is specially：
Single base radar positioned at default sampled point sends radar detection signal to object under test, receives the inside of object under test
The one-dimensional Wave data of each dieletric reflection radar detection signal；
Based on default sampled point, the one-dimensional Wave data of multiple sampled points, multiple one-dimensional waves are obtained in the first preset direction
Graphic data forms two-dimensional radar waveform dataset.
In some embodiments, medium accounting computing module can include：
Area is than calculating sub module, for calculating the regional in several internal structure cross-sectional images and internal structure respectively
Make the area ratio of cross-sectional image；
Mean value calculation submodule, for multiple area ratios in the region according to corresponding to each medium, it is calculated each
The area in region is than average value, and using composition accounting of the area than average value as respective media.
In some embodiments, the device can also include：
Interior three-dimensional model construction module, for utilizing the multiple two dimensions obtained on the second preset direction in pre-determined distance
Internal structure cross-sectional image, form the interior three-dimensional model of object under test；Or
Interior three-dimensional model inverter module, for detecting object under test simultaneously and obtaining according to being distributed radar using more base arrays
Three-dimensional radar Wave data, by radar signal inversion imaging, draw the interior three-dimensional model of object under test；
Medium volume computing module, for the volume of each medium according to interior three-dimensional model and area ratio, to be calculated.
In some embodiments, image segmentation module can include：
Split submodule, for using in gray threshold segmentation algorithm, Region Segmentation Algorithm or rim detection partitioning algorithm
It is any, a kind of pixel of medium will be belonged to and be divided to the same area, internal structure cross-sectional image is divided into more
Individual region.
In some embodiments, the device can also include：
Image pre-processing module, for carrying out image pretreatment operation to internal structure cross-sectional image；
Wherein, image pretreatment operation comprise at least Slant Rectify, cut, denoising, enhancing and rasterizing.
The interior of articles component detecting device that the present embodiment is provided, the device are carried out Wave data using signal inverting
Inverting, the internal structure cross-sectional image of object under test is drawn, so as to detect the internal structure of object under test；Then figure is utilized
As internal structure cross-sectional image is divided into multiple regions by segmentation, the pixel in each region belongs to a kind of medium, i.e. area
Each medium inside object under test is separated；Then whole internal structure cross-sectional image is accounted for by calculating each areas of dielectric
Area ratio, the ratio shared by each medium inside object under test is drawn.
Example IV
The interior of articles component detection system provided the present embodiment is described in detail below, referring to shown in Fig. 8
The structural schematic block diagram of interior of articles component detection system provided in an embodiment of the present invention, the system can include detecting devices 81
And processing terminal 82；
Detecting devices 81 is used for the detectable signal for possessing penetrability to the transmitting of opaque object under test and receives detectable signal
Wave data through each dieletric reflection inside object under test, and Wave data is sent to processing terminal；
Processing terminal 82 is used to receive Wave data；According to Wave data, by signal inversion imaging, object under test is drawn
Internal structure cross-sectional image；Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, with
Internal structure cross-sectional image is divided into multiple regions；The area ratio of regional and internal structure cross-sectional image is calculated respectively,
Draw the composition accounting of each medium inside object under test.
Preferably, processing terminal can be also used for the composition accounting according to each medium, calculate each inside object under test
The volume of individual medium.Detailed process may refer to corresponding contents above, will not be repeated here.
Preferably, detecting devices is GPR, and detectable signal is high frequency electromagnetic wave signal.Now, single radar and more
The detailed process of individual radar detection object may refer to corresponding contents above, will not be repeated here.
It is to be appreciated that above-mentioned processing terminal can be specially the intelligent terminals such as computer.And the system also includes showing
Show equipment, data transmission module and other necessary support modules.The present embodiment and the similar portion of above-mentioned each embodiment can phases
Mutually referring to will not be repeated here.
In the present embodiment, interior of articles component detection system, using signal inversion imaging, is drawn to be measured according to Wave data
The internal structure cross-sectional image of object, so as to detect the internal structure of object under test；Split using image by internal structure
Cross-sectional image is divided into multiple regions, and the pixel in each region belongs to a kind of medium, that is, has distinguished in object under test
Each medium in portion；The area ratio of whole internal structure cross-sectional image is accounted for by calculating each areas of dielectric, has drawn determinand
Ratio shared by each medium in internal portion.
Each embodiment is described by the way of progressive in specification, and what each embodiment stressed is and other realities
Apply the difference of example, between each embodiment identical similar portion mutually referring to.For device disclosed in embodiment
Speech, because it is corresponded to the method disclosed in Example, so description is fairly simple, related part is referring to method part illustration
.
Professional further appreciates that, with reference to the unit of each example of the embodiments described herein description
And algorithm steps, can be realized with electronic hardware, computer software or the combination of the two, in order to clearly demonstrate hardware and
The interchangeability of software, the composition and step of each example are generally described according to function in the above description.These
Function is performed with hardware or software mode actually, application-specific and design constraint depending on technical scheme.Specialty
Technical staff can realize described function using distinct methods to each specific application, but this realization should not
Think beyond the scope of this invention.
Directly it can be held with reference to the step of method or algorithm that the embodiments described herein describes with hardware, processor
Capable software module, or the two combination are implemented.Software module can be placed in random access memory (RAM), internal memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
Interior of articles component detection method, apparatus provided by the present invention and system are described in detail above.This
Apply specific case in text to be set forth the principle and embodiment of the present invention, the explanation of above example is only intended to
Help to understand method and its core concept of the invention.It should be pointed out that for those skilled in the art,
Without departing from the principles of the invention, some improvement and modification can also be carried out to the present invention, these are improved and modification also falls
Enter in the protection domain of the claims in the present invention.
Claims (15)
- A kind of 1. interior of articles component detection method, it is characterised in that including：Wave data is obtained, the Wave data possesses penetrability detection by detecting devices to what opaque object under test was launched Signal data of the signal after each dieletric reflection inside the object under test；According to the Wave data, by signal inversion imaging, the internal structure cross-sectional image of the object under test is drawn；Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, by the internal structure Cross-sectional image is divided into multiple regions；The area ratio in each region and the internal structure cross-sectional image is calculated respectively, is drawn each inside the object under test The composition accounting of the individual medium.
- 2. interior of articles component detection method as claimed in claim 1, it is characterised in that it is described according to the Wave data, By signal inversion imaging, the internal structure cross-sectional image of the object under test is drawn, including：According to two-dimensional radar Wave data, by radar signal inversion imaging, the two-dimentional internal structure of the object under test is drawn Cross-sectional image；Wherein, the two-dimensional radar Wave data is to detect the object under test simultaneously using more baseline linear distribution radars to obtain Data, or single base radar individually detects the data that the object under test obtains；The process that single base radar individually detects the object under test is specially：Single base radar positioned at default sampled point sends radar detection signal to the object under test, receives the determinand The one-dimensional Wave data of each dieletric reflection in inside of body；Based on the default sampled point, the one-dimensional Wave data of multiple sampled points, Duo Gesuo are obtained in the first preset direction State one-dimensional Wave data and form two-dimensional radar waveform dataset.
- 3. interior of articles component detection method as claimed in claim 1, it is characterised in that described to calculate each area respectively Domain and the area ratio of the internal structure cross-sectional image, the composition accounting of each medium inside the object under test is drawn, Including：Each region in several described internal structure cross-sectional images and the internal structure cross-sectional image are calculated respectively The area ratio；According to multiple area ratios in the region corresponding to each medium, the area in each region is calculated Than average value, and using the composition accounting of the area than average value as the corresponding medium.
- 4. the interior of articles component detection method as described in any one of claims 1 to 3, it is characterised in that counted respectively described The area ratio in each region and the internal structure cross-sectional image is calculated, draws each medium inside the object under test Composition accounting after, in addition to：Using the multiple two-dimentional internal structure cross-sectional images obtained on the second preset direction in pre-determined distance, described in composition The interior three-dimensional model of object under test；According to the interior three-dimensional model and area ratio, the volume of each medium is calculated；OrAccording to being distributed radar using more base arrays while detecting the three-dimensional radar Wave data of the object under test acquisition, pass through Radar signal inversion imaging, draw the interior three-dimensional model of the object under test；According to the interior three-dimensional model and area ratio, the volume of each medium is calculated.
- 5. interior of articles component detection method as claimed in claim 4, it is characterised in that it is described to utilize image segmentation algorithm, A kind of pixel of medium will be belonged to and be divided to the same area, the internal structure cross-sectional image is divided into multiple areas Domain, including：Using any of gray threshold segmentation algorithm, Region Segmentation Algorithm or rim detection partitioning algorithm, one will be belonged to The pixel of kind medium is divided to the same area, and the internal structure cross-sectional image is divided into multiple regions.
- 6. interior of articles component detection method as claimed in claim 5, it is characterised in that it is described by signal inverting into Picture, inverting is carried out to the Wave data, after drawing the internal structure cross-sectional image of the object under test, split using image Algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, the internal structure cross-sectional image is divided into more Before individual region, in addition to：Image pretreatment operation is carried out to the internal structure cross-sectional image；Wherein, described image pretreatment operation comprise at least Slant Rectify, cut, denoising, enhancing and rasterizing.
- A kind of 7. interior of articles component detecting device, it is characterised in that including：Acquisition module, for obtaining Wave data, the Wave data is launched by detecting devices to opaque object under test Possess signal data of the penetrability detectable signal after each dieletric reflection inside the object under test；Inversion imaging module, for according to the Wave data, by signal inversion imaging, draw the inside of the object under test Structure sectional view picture；Image segmentation module, for using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to the same area, So that the internal structure cross-sectional image is divided into multiple regions；Medium accounting computing module, for calculating the area ratio in each region and the internal structure cross-sectional image respectively, Draw the composition accounting of each medium inside the object under test.
- 8. interior of articles component detecting device as claimed in claim 7, it is characterised in that the inversion imaging module includes：Radar inversion imaging submodule, for according to two-dimensional radar Wave data, by radar signal inversion imaging, drawing described The two-dimentional internal structure cross-sectional image of object under test；Wherein, the two-dimensional radar Wave data is to detect the object under test simultaneously using more baseline linear distribution radars to obtain Data, or single base radar individually detects the data that the object under test obtains；The process that single base radar individually detects the object under test is specially：Single base radar positioned at default sampled point sends radar detection signal to the object under test, receives the determinand The one-dimensional Wave data of radar detection signal described in each dieletric reflection in inside of body；Based on the default sampled point, the one-dimensional Wave data of multiple sampled points, Duo Gesuo are obtained in the first preset direction State one-dimensional Wave data and form two-dimensional radar waveform dataset.
- 9. interior of articles component detecting device as claimed in claim 7, it is characterised in that the medium accounting computing module bag Include：Area is than calculating sub module, for calculating each region and institute in several described internal structure cross-sectional images respectively State the area ratio of internal structure cross-sectional image；Mean value calculation submodule, for multiple area ratios in the region according to corresponding to each medium, calculate The area in each region is drawn than average value, and using the composition of the area than average value as the corresponding medium Accounting.
- 10. the interior of articles component detecting device as described in any one of claim 7 to 9, it is characterised in that also include：Interior three-dimensional model construction module, for utilizing the multiple two dimensions obtained on the second preset direction in pre-determined distance Internal structure cross-sectional image, form the interior three-dimensional model of the object under test；OrInterior three-dimensional model inverter module, for detecting the object under test simultaneously and obtaining according to being distributed radar using more base arrays Three-dimensional radar Wave data, by radar signal inversion imaging, draw the interior three-dimensional model of the object under test；Medium volume computing module, for according to the interior three-dimensional model and area ratio, each given an account of to be calculated The volume of matter.
- 11. interior of articles component detecting device as claimed in claim 10, it is characterised in that described image splits module bag Include：Split submodule, for utilizing appointing in gray threshold segmentation algorithm, Region Segmentation Algorithm or rim detection partitioning algorithm One kind, a kind of pixel of medium will be belonged to and be divided to the same area, the internal structure cross-sectional image is divided into more The individual region.
- 12. interior of articles component detecting device as claimed in claim 11, it is characterised in that also include：Image pre-processing module, for carrying out image pretreatment operation to the internal structure cross-sectional image；Wherein, described image pretreatment operation comprise at least Slant Rectify, cut, denoising, enhancing and rasterizing.
- 13. a kind of interior of articles component detection system, it is characterised in that including detecting devices and processing terminal；Detectable signal and the reception detection that the detecting devices is used to possess penetrability to the transmitting of opaque object under test are believed Number Wave data through each dieletric reflection inside the object under test, and the Wave data is sent to the processing terminal；The processing terminal is used to receive the Wave data；According to the Wave data, by signal inversion imaging, institute is drawn State the internal structure cross-sectional image of object under test；Using image segmentation algorithm, a kind of pixel of medium will be belonged to and be divided to The same area, the internal structure cross-sectional image is divided into multiple regions；Calculate respectively each region with it is described interior The area ratio of cage structure cross-sectional image, draw the composition accounting of each medium inside the object under test.
- 14. interior of articles component detection system as claimed in claim 13, it is characterised in that the processing terminal is additionally operable to root According to the composition accounting of each medium, the volume of each medium inside the object under test is calculated.
- 15. interior of articles component detection system as claimed in claim 14, it is characterised in that the detecting devices is spy land mine Reach, the detectable signal is high frequency electromagnetic wave signal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710800746.4A CN107589420A (en) | 2017-09-07 | 2017-09-07 | A kind of interior of articles component detection method, apparatus and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710800746.4A CN107589420A (en) | 2017-09-07 | 2017-09-07 | A kind of interior of articles component detection method, apparatus and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107589420A true CN107589420A (en) | 2018-01-16 |
Family
ID=61051325
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710800746.4A Pending CN107589420A (en) | 2017-09-07 | 2017-09-07 | A kind of interior of articles component detection method, apparatus and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107589420A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108680137A (en) * | 2018-04-24 | 2018-10-19 | 天津职业技术师范大学 | Earth subsidence detection method and detection device based on unmanned plane and Ground Penetrating Radar |
| CN110132961A (en) * | 2018-02-09 | 2019-08-16 | 宝山钢铁股份有限公司 | The quickly method of gypsum lime stone and flue dust ratio in measurement desulphurization circulating slurries |
| CN110782464A (en) * | 2019-11-04 | 2020-02-11 | 浙江大华技术股份有限公司 | Calculation method of object accumulation 3D space occupancy rate, coder-decoder and storage device |
| CN111680733A (en) * | 2020-06-01 | 2020-09-18 | 北京建工资源循环利用投资有限公司 | Component detection method, sample library establishment method, device, platform, system and medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105204032A (en) * | 2015-09-29 | 2015-12-30 | 中国人民解放军装备学院 | Laser detection system for three-dimensional imaging of moving object and imaging method |
| CN106296653A (en) * | 2016-07-25 | 2017-01-04 | 浙江大学 | Brain CT image hemorrhagic areas dividing method based on semi-supervised learning and system |
-
2017
- 2017-09-07 CN CN201710800746.4A patent/CN107589420A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105204032A (en) * | 2015-09-29 | 2015-12-30 | 中国人民解放军装备学院 | Laser detection system for three-dimensional imaging of moving object and imaging method |
| CN106296653A (en) * | 2016-07-25 | 2017-01-04 | 浙江大学 | Brain CT image hemorrhagic areas dividing method based on semi-supervised learning and system |
Non-Patent Citations (2)
| Title |
|---|
| 刘人硕: "基于三维扫描技术的木材缺陷检测技术研究与应用", 《中国优秀硕士学位论文全文数据库 农业科技辑》 * |
| 向伟: "基于探地雷达城市地下空间图像的探测识别研究", 《中国优秀硕士学位论文全文数据库 基础科学辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110132961A (en) * | 2018-02-09 | 2019-08-16 | 宝山钢铁股份有限公司 | The quickly method of gypsum lime stone and flue dust ratio in measurement desulphurization circulating slurries |
| CN108680137A (en) * | 2018-04-24 | 2018-10-19 | 天津职业技术师范大学 | Earth subsidence detection method and detection device based on unmanned plane and Ground Penetrating Radar |
| CN110782464A (en) * | 2019-11-04 | 2020-02-11 | 浙江大华技术股份有限公司 | Calculation method of object accumulation 3D space occupancy rate, coder-decoder and storage device |
| CN110782464B (en) * | 2019-11-04 | 2022-07-15 | 浙江大华技术股份有限公司 | Calculation method of object accumulation 3D space occupancy rate, coder-decoder and storage device |
| CN111680733A (en) * | 2020-06-01 | 2020-09-18 | 北京建工资源循环利用投资有限公司 | Component detection method, sample library establishment method, device, platform, system and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109583293B (en) | Aircraft target detection and identification method in satellite-borne SAR image | |
| CN107589420A (en) | A kind of interior of articles component detection method, apparatus and system | |
| Gonzalez-Huici et al. | A combined strategy for landmine detection and identification using synthetic GPR responses | |
| CN106446919B (en) | A kind of Ground Penetrating Radar hyperbolic line target rapid detection method | |
| Drews et al. | Validation of fracture data recognition in rock masses by automated plane detection in 3D point clouds | |
| Luo et al. | GPR pattern recognition of shallow subsurface air voids | |
| CN103268496A (en) | Target identification method of SAR (synthetic aperture radar) images | |
| Ristić et al. | Point coordinates extraction from localized hyperbolic reflections in GPR data | |
| CN112324422B (en) | Electric imaging logging fracture and hole identification method, system and pore structure characterization method | |
| CN104730148A (en) | Metal material inner inclusion three-dimensional reconstruction method based on ultrasonic testing technology | |
| CN108333634A (en) | A kind of Ground Penetrating Radar buried target localization method based on frequency spectrum remnants conspicuousness detection methods | |
| Liu et al. | The target detection for GPR images based on curve fitting | |
| Qin et al. | Bidimensional empirical mode decomposition method for image processing in sensing system | |
| Guo et al. | KD-tree-based euclidean clustering for tomographic SAR point cloud extraction and segmentation | |
| CN114419542A (en) | Millimeter wave image detection optimal model selection method and device based on deep learning | |
| CN107835998A (en) | For identifying the layering Tiling methods of the surface type in digital picture | |
| Milisavljević et al. | Improving mine recognition through processing and Dempster–Shafer fusion of ground-penetrating radar data | |
| Al-Nuaimy et al. | Automatic detection of hyperbolic signatures in ground-penetrating radar data | |
| Shihab et al. | Image processing and neural network techniques for automatic detection and interpretation of ground penetrating radar data | |
| Gaikwad et al. | Recognition of target in through wall imaging using shape feature extraction | |
| CN106897985B (en) | A kind of multi-angle SAR image fusion method based on visibility classification | |
| Voccola et al. | On the relationship between the generalized likelihood ratio test and backprojection for synthetic aperture radar imaging | |
| CN115201816A (en) | Three-dimensional ground penetrating radar quantitative imaging method based on improved backward projection | |
| Catakli et al. | Texture analysis of GPR data as a tool for depicting soil mineralogy | |
| Al-Nuaimy et al. | Automatic target detection in GPR data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20180116 |
|
| WD01 | Invention patent application deemed withdrawn after publication |