CN110751059A - Least square method-based finger vein ROI extraction method, device and storage medium - Google Patents
Least square method-based finger vein ROI extraction method, device and storage medium Download PDFInfo
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- 238000003708 edge detection Methods 0.000 claims abstract description 18
- 210000001503 joint Anatomy 0.000 claims description 11
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Abstract
The invention discloses a method, a device, equipment and a storage medium for extracting a finger vein ROI based on a least square method, wherein the method comprises the following steps: detecting the edge of the target detection finger; performing rotation correction on the edge information of the detected target finger; intercepting information of a target finger inscribing area; finding the finger joint position of the corrected target finger information; and intercepting the ROI information through the finger joint position. Detecting the edge of the finger through an upper edge detection operator and a lower edge detection operator, then carrying out rotation correction, then intercepting an inscribed region of the finger, finally searching the position of a finger joint, and intercepting a corresponding ROI according to the position of the finger joint; the method can effectively reduce the processing time of identification, improve the identification degree and have robustness.
Description
Technical Field
The invention relates to the field of image processing, in particular to a method, a device, equipment and a storage medium for extracting a finger vein ROI based on a least square method.
Background
At present, people have higher and higher requirements on identity identification, and finger vein identification is a new biometric identification technology and draws wide attention in the field of biometric authentication. Compared with other biometric identification technologies (such as human face, gait and fingerprint), the finger vein technology has some obvious advantages: such as higher user-friendliness, activity detection, high safety and small device size, which makes it very suitable for high-safety and user-friendly applications. In a finger vein recognition system, due to the movement and rotation of a finger on a finger vein image capture device, the vein lines in a registered image are inconsistent with a recognition image, the recognition performance is influenced, the recognition accuracy is low, and the like.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a method, a device, equipment and a storage medium for extracting a finger vein ROI based on a least square method, so that the processing time of identification is effectively reduced, the identification degree is improved, and the robustness is realized.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, the present invention provides a method for extracting a finger vein ROI based on a least square method, comprising the steps of:
detecting the edge of the target detection finger;
performing rotation correction on the edge information of the detected target finger;
intercepting information of a target finger inscribing area;
finding the finger joint position of the corrected target finger information;
and intercepting the ROI information through the finger joint position.
Further, the detecting the edge of the target detection finger includes: and performing Gaussian low-pass filtering on the edge image of the target detection finger to remove noise, and obtaining different upper and lower edge detection operators by adopting a template in the vertical direction in a Prewitt operator according to the actual situation of bright-dark contrast at the two sides of the upper and lower edges of the finger.
Further, the performing rotation correction on the edge information of the detected target finger includes: and calculating the midpoint coordinates of the upper and lower edge abscissa point pairs along the horizontal direction of the target finger detection information, forming the central axis of the finger by using the coordinate points fitted by the least square method, and finishing rotation correction by calculating the included angle between the central axis and the horizontal direction.
Further, the intercepting information of the target finger inscribing area includes: and (3) by detecting the point coordinates of the upper edge line and the lower edge line which are subjected to rotation correction and are closest to the central axis of the finger, making two tangent lines from the positions of the point coordinates, and intercepting the original image by utilizing the two tangent lines to obtain an image of the internally tangent region of the finger.
Further, the finding of the knuckle position for the corrected target finger information includes: and acquiring a horizontal direction brightness change trend graph of the image of the finger inscribing area by using a sliding window summation method, and intercepting a peak of the horizontal direction brightness change trend graph to obtain the position of the phalangeal joint.
Further, the intercepting the ROI information by the knuckle position includes: the position of the distal interphalangeal joint, that is, the position of the interphalangeal joint close to the fingertip is detected in the finger vein image, and a two-thirds wide region is cut on each of both sides of the detected position as a cut ROI region with the detected position as a reference.
In a second aspect, the present invention provides a device for extracting a finger vein ROI based on a least square method, comprising:
a detection unit for detecting an edge of a target detection finger;
a correction unit configured to perform rotation correction on edge information of the detected target finger;
the intercepting unit is used for intercepting the information of the internally tangent region of the target finger;
the positioning unit is used for searching the finger joint position for the corrected target finger information;
and the acquisition unit is used for intercepting and obtaining the ROI information through the finger joint position.
In a third aspect, the present invention provides a device for finger vein ROI extraction based on least squares, comprising at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the method of vein identification described above.
In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the method for least squares based finger vein ROI extraction as described above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program stored on a computer-readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method for least squares based finger vein ROI extraction as described above.
One or more technical schemes provided in the embodiment of the invention have at least the following beneficial effects:
detecting the edge of the finger through an upper edge detection operator and a lower edge detection operator, then carrying out rotation correction, then intercepting an inscribed region of the finger, finally searching the position of a finger joint, and intercepting a corresponding ROI according to the position of the finger joint; the method can effectively reduce the processing time of identification, improve the identification degree and have robustness.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of one embodiment of a method for extracting a finger vein ROI based on a least square method according to an embodiment of the invention;
FIG. 2 is an upper edge detection subgraph of the method for extracting the ROI of the finger vein based on the least square method provided by the embodiment of the invention;
fig. 3 is a lower edge detection subgraph of the method for extracting the ROI of the finger vein based on the least square method according to the embodiment of the present invention;
fig. 4 is an original image read by a method for extracting a finger vein ROI based on a least square method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of edge detection with false edges of a method for extracting a finger vein ROI based on a least square method according to an embodiment of the invention;
FIG. 6 is an edge detection diagram for removing false edges of a least square method-based method for extracting ROI of finger veins provided by an embodiment of the invention;
FIG. 7 is a schematic diagram of a centerline fitting of a least-squares based method for extracting ROI from finger veins according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of rotation correction with black filled regions for a least-squares based method of finger vein ROI extraction according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of the rotation correction of the removed black filled region according to the least square method for extracting the ROI of the finger vein;
FIG. 10 is a schematic diagram of a cut-out finger incision area of a method for extracting a finger vein ROI based on a least square method according to an embodiment of the invention;
FIG. 11 is a diagram of an intra-finger region of a method for extracting a finger vein ROI based on a least square method according to an embodiment of the present invention;
FIG. 12 is a diagram illustrating the horizontal luminance variation trend of the least-squares-based method for extracting ROI from finger veins according to the embodiment of the present invention;
FIG. 13 is a schematic diagram of a ROI clipping position of a method for extracting a finger vein ROI based on a least square method according to an embodiment of the invention;
FIG. 14 is a schematic diagram of a truncated ROI of a method for extracting a finger vein ROI based on a least square method provided by an embodiment of the invention;
FIG. 15 is a diagram of ROI + CLAHE of the method for extracting finger vein ROI based on least square method provided by the embodiment of the invention;
FIG. 16 is a diagram of ROI + CLAHE + Gabor of the method for extracting finger vein ROI based on least square method according to the embodiment of the present invention;
FIG. 17 is a schematic structural diagram of an apparatus for a least-squares-based method for extracting ROI from finger veins according to an embodiment of the present invention;
fig. 18 is a schematic structural diagram of a device of a method for extracting a finger vein ROI based on a least square method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
It should be noted that, if not conflicted, the various features of the embodiments of the invention may be combined with each other within the scope of protection of the invention. Additionally, while functional block divisions are performed in apparatus schematics, with logical sequences shown in flowcharts, in some cases, steps shown or described may be performed in sequences other than block divisions in apparatus or flowcharts.
Referring to fig. 1, the method for extracting a finger vein ROI based on a least square method according to an embodiment of the present invention includes the following steps:
detecting the edge of the target detection finger;
performing rotation correction on the edge information of the detected target finger;
intercepting information of a target finger inscribing area;
finding the finger joint position of the corrected target finger information;
and intercepting the ROI information through the finger joint position.
Detecting the edge of the finger through an upper edge detection operator and a lower edge detection operator, then carrying out rotation correction, then intercepting an inscribed region of the finger, finally searching the position of a finger joint, and intercepting a corresponding ROI according to the position of the finger joint; the method can effectively reduce the processing time of identification, improve the identification degree and have robustness.
The method for extracting the finger vein ROI based on the least square method comprises the following steps of: and performing Gaussian low-pass filtering on the edge image of the target detection finger to remove noise, and obtaining different upper and lower edge detection operators by adopting a template in the vertical direction in a Prewitt operator according to the actual situation of bright-dark contrast at the two sides of the upper and lower edges of the finger.
In the method for extracting a finger vein ROI based on the least square method according to the embodiment of the present invention, the performing rotation correction on the edge information of the detected target finger includes: and calculating the midpoint coordinates of the upper and lower edge abscissa point pairs along the horizontal direction of the target finger detection information, forming the central axis of the finger by using the coordinate points fitted by the least square method, and finishing rotation correction by calculating the included angle between the central axis and the horizontal direction.
The method for extracting the finger vein ROI based on the least square method comprises the following steps of: and (3) by detecting the point coordinates of the upper edge line and the lower edge line which are subjected to rotation correction and are closest to the central axis of the finger, making two tangent lines from the positions of the point coordinates, and intercepting the original image by utilizing the two tangent lines to obtain an image of the internally tangent region of the finger.
The method for extracting the finger vein ROI based on the least square method comprises the following steps of: and acquiring a horizontal direction brightness change trend graph of the image of the finger inscribing area by using a sliding window summation method, and intercepting a peak of the horizontal direction brightness change trend graph to obtain the position of the phalangeal joint.
The method for extracting the ROI of the finger vein based on the least square method comprises the following steps of: the position of the distal interphalangeal joint, that is, the position of the interphalangeal joint close to the fingertip is detected in the finger vein image, and a two-thirds wide region is cut on each of both sides of the detected position as a cut ROI region with the detected position as a reference.
The method comprises the steps of detecting the edge of a finger through an upper edge detection operator and a lower edge detection operator, then carrying out rotation correction, then intercepting an internally tangent region of the finger, finally searching the position of a finger joint, and intercepting a corresponding ROI according to the position of the finger joint.
Referring to fig. 2-3, finger edge detection: firstly, Gaussian low-pass filtering is carried out on the image to remove noise, then a template in the vertical direction in a Prewitt operator is adopted, and different upper and lower edge detection operators are obtained according to the actual situation of bright-dark contrast on the two sides of the upper and lower edges of the finger.
Referring to fig. 4-7, after the finger edge detection, there are some false edges in addition to the upper and lower edges of the real finger, and experiments verify that the pixel number values in the false edge connected region are all smaller than the connected domain pixel number values of the real edge of the finger, so that only two maximum connected domains in the detection result are reserved as the edges of the finger, and the false edges are removed.
Referring to fig. 8-9, rotation correction: the finger is prone to in-plane rotation at acquisition, which needs to be corrected to avoid affecting ROI extraction. Firstly, calculating the coordinates of the middle points of the upper and lower edge abscissa point pairs along the horizontal direction, then fitting the coordinate points into a straight line by using a least square method, namely the central axis of the finger, and finishing rotation correction by calculating the included angle between the central axis and the horizontal direction. Black filled regions are generated at the boundaries during the correction process due to image rotation, so we perform a bicubic interpolation operation on them.
Least square method: suppose something (x)1,y1),(x2,y2)...(xn,yn) We aim to minimize the sum of the squared deviations of the values on the fitted line y ═ ax + b from the actual values:
referring to fig. 10-11, the inscribed finger region is cut: the finger inscribed region is cut out on the original image by detecting the coordinates of the point of the upper edge line and the lower edge line which are closest to the midpoint of the rotation-corrected upper edge line and the lower edge line, then making two tangent lines l1 and l2 from the positions of the point, and finally utilizing the two tangent lines.
Referring to fig. 12-13, finding knuckle positions: the method comprises the steps of obtaining the horizontal brightness change trend of an image of an internal tangent region of a finger by using a sliding window summation method, wherein the height of a sliding window is the same as the height of the image of the internal tangent region, the width of the sliding window is one-thirtieth of the width of the image of the internal tangent region, and the sum of pixel values in each window is calculated while the window is slid along the horizontal direction, so that the overall brightness change trend graph of the finger vein image in the horizontal direction is obtained. Because the mean brightness of the interphalangeal joint area is greater than the rest of the finger, we can use this feature to locate the interphalangeal joint. It can be seen from the figure that the horizontal brightness variation trend has two peaks, namely the positions of two phalangeal joints.
Referring to fig. 14-16, the ROI region is truncated: the position of the distal interphalangeal joint, that is, the position of the interphalangeal joint close to the fingertip is detected in the finger vein image, and a two-thirds wide region is cut on each of both sides of the detected position as a cut ROI region with the detected position as a reference. Secondly, in order to facilitate the preparation of a label of vein lines in the subsequent process, Limited Contrast Adaptive Histogram Equalization (CLAHE) processing is carried out on the intercepted ROI, and the method has very obvious enhancement effect on medical images, particularly medical infrared images. The CLAHE not only has the characteristic of local histogram equalization and is suitable for the difference of the gray distribution of different parts of the image, but also has the effect of more coordinated gray distribution of global histogram equalization, and can effectively inhibit the enhancement of noise, but nevertheless, part of noise still exists, so Gabor filtering is used on the basis to filter the noise after the image enhancement, and the filtered ROI image is taken as the reference to manufacture the label for neural network training.
The traditional image enhancement method has great limitations, such as global enhancement of the image by histogram equalization, noise increase or new noise introduction. Although the defect that global histogram Equalization is difficult to adapt to local gray distribution is overcome, local histogram Equalization, namely an Adaptive Histogram Equalization (AHE), has an obvious blocking effect after Equalization. CLAHE is to obtain a new gray image by a bilinear interpolation method at the corresponding positions of two adjacent areas when local histograms are balanced. Wherein, the basic flow of the CLAHE algorithm is as follows:
1. the original image is divided into M × N continuous non-overlapping sub-regions.
2. The gray histogram "cut" is performed for each sub-region, and the average value of the number of evenly distributed pixels is calculated.
In the formula, N _ XY is the gray level number of the sub-area; μ _ X and μ _ Y are the number of pixels in the two directions of the sub-areas X and Y, respectively.
Calculating the actual shear limit: l isC＝NClipAV
In the formula, NCilpIs the set "shear" limiting factor.
The total number of the clipped pixels is S, and the number of the clipped pixels is divided equally
Calculating the step length of distributing the residual pixel number
Wherein L is the step length of the distributed pixels; l isGIs the length of the gray scale range.
And searching from the minimum gray level to the maximum gray level in a step-length cycle, and allocating one pixel at the position where the pixel is smaller than the shearing threshold value. If there are more remaining pixels, the step size and the loop search are recalculated until the remaining pixels are assigned.
3. And equalizing the gray level histogram after the contrast of each subarea is limited.
4. The center point of each sub-region is obtained and these points are taken as sample points.
5. Performing gray scale linear interpolation, i.e.
G(i)＝a[bGzs(i)+(1-b)Gzx(i)]+(1-a)[bGyx(i)+(1-b)Gys(i)]
Wherein G (i) is the gray scale value at point (x, y); gzs(i) The sample point at the upper left of the evaluation point; gzx(i)，Gyx(i)，Gys(i) Respectively, the other 3 azimuth sample points. The gray level of the pixels outside the peripheral sample points is linearly interpolated by using the adjacent 2 sample points, and the point at the 4 corners of the image is calculated by using the adjacent 1 sample point.
Referring to fig. 17, an embodiment of the present invention further provides a vein recognition apparatus, including:
a detection unit 1100 for detecting an edge of a target detection finger;
a correction unit 1200 for performing rotation correction on the edge information of the detected target finger;
an intercepting unit 1300 configured to intercept information of a region inscribed in a target finger;
the positioning unit 1400 is used for searching the corrected target finger information for the finger joint position;
an obtaining unit 1500, configured to obtain the ROI information by intercepting the finger joint position.
It should be noted that, since the vein identification apparatus in the present embodiment is based on the same inventive concept as the vein identification method described above, the corresponding contents in the method embodiment are also applicable to the present apparatus embodiment, and are not described in detail herein.
Referring to fig. 18, an embodiment of the present invention further provides a vein recognition device, and the vein recognition device 200 may be any type of smart terminal, such as a mobile phone, a tablet computer, a personal computer, and the like.
Specifically, the vein recognition apparatus 200 includes: one or more control processors 201 and a memory 202, and one control processor 201 is illustrated in fig. 18.
The control processor 201 and the memory 202 may be connected by a bus or other means, and fig. 18 illustrates the connection by a bus as an example.
The memory 202, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the vein identification method in the embodiment of the present invention, for example, the detection unit 1100, the correction unit 1200, the interception unit 1300, the positioning unit 1400, and the acquisition unit 1500 shown in fig. 17. The control processor 201 executes various functional applications and data processing of the vein recognition apparatus 1000, i.e. the method of vein recognition, by running non-transitory software programs, instructions and modules stored in the memory 202, i.e. implementing the above-described method embodiments.
The memory 202 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created from use of the vein recognition apparatus 1000, and the like. Further, the memory 202 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 202 may optionally include memory remotely located from the control processor 201, which may be connected to the vein recognition device 200 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 202, and when executed by the one or more control processors 201, perform the method for vein identification in the above-described method embodiments, e.g., perform the above-described method steps S10-S50 in fig. 1, and implement the functions of the unit 1100-1500 in fig. 17.
Embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions, which are executed by one or more control processors, for example, by one control processor 201 in fig. 18, and can cause the one or more control processors 201 to execute the vein identification method in the above method embodiment, for example, execute the above-described method steps S10 to S50 in fig. 1, and implement the functions of the unit 1100-1500 in fig. 17.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by software plus a general hardware platform. Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, and the program may be stored in a computer readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
While the preferred embodiments of the present invention have been described in detail, it will be understood by those skilled in the art that the foregoing and various other changes, omissions and deviations in the form and detail thereof may be made without departing from the scope of this invention.
Claims (9)
1. A method for extracting a finger vein ROI based on a least square method is characterized in that: the method comprises the following steps:
detecting the edge of the target detection finger;
performing rotation correction on the edge information of the detected target finger;
intercepting information of a target finger inscribing area;
finding the finger joint position of the corrected target finger information;
and intercepting the ROI information through the finger joint position.
2. The method of least squares based finger vein ROI extraction of claim 1, wherein: the detecting the edge of the target detection finger comprises: and performing Gaussian low-pass filtering on the edge image of the target detection finger to remove noise, and obtaining different upper and lower edge detection operators by adopting a template in the vertical direction in a Prewitt operator according to the actual situation of bright-dark contrast at the two sides of the upper and lower edges of the finger.
3. The method of least squares based finger vein ROI extraction of claim 1, wherein: the performing rotation correction on the edge information of the detected target finger comprises: and calculating the midpoint coordinates of the upper and lower edge abscissa point pairs along the horizontal direction of the target finger detection information, forming the central axis of the finger by using the coordinate points fitted by the least square method, and finishing rotation correction by calculating the included angle between the central axis and the horizontal direction.
4. The method of least squares based finger vein ROI extraction of claim 1, wherein: the intercepting information of the target finger inscribing area comprises the following steps: and (3) by detecting the point coordinates of the upper edge line and the lower edge line which are subjected to rotation correction and are closest to the central axis of the finger, making two tangent lines from the positions of the point coordinates, and intercepting the original image by utilizing the two tangent lines to obtain an image of the internally tangent region of the finger.
5. The method of least squares based finger vein ROI extraction according to claim 4, wherein: the searching for the knuckle position for the corrected target finger information includes: and acquiring a horizontal direction brightness change trend graph of the image of the finger inscribing area by using a sliding window summation method, and intercepting a peak of the horizontal direction brightness change trend graph to obtain the position of the phalangeal joint.
6. The method of least squares based finger vein ROI extraction of claim 1, wherein: the intercepting of the ROI information through the finger joint positions comprises the following steps: the position of the distal interphalangeal joint, that is, the position of the interphalangeal joint close to the fingertip is detected in the finger vein image, and a two-thirds wide region is cut on each of both sides of the detected position as a cut ROI region with the detected position as a reference.
7. Device of finger vein ROI extraction based on least square method, its characterized in that: the method comprises the following steps:
a detection unit for detecting an edge of a target detection finger;
a correction unit configured to perform rotation correction on edge information of the detected target finger;
the intercepting unit is used for intercepting the information of the internally tangent region of the target finger;
the positioning unit is used for searching the finger joint position for the corrected target finger information;
and the acquisition unit is used for intercepting and obtaining the ROI information through the finger joint position.
8. Device of finger vein ROI extraction based on least square method, its characterized in that: comprises at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the method of least squares based finger vein ROI extraction of any one of claims 1-6.
9. A computer-readable storage medium characterized by: the computer-readable storage medium stores computer-executable instructions for causing a computer to perform the method for least squares based finger vein ROI extraction of any one of claims 1-6.
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|---|---|---|---|---|
| CN114882539A (en) * | 2022-07-11 | 2022-08-09 | 山东圣点世纪科技有限公司 | Vein image ROI extraction method and device |
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