CN105975911A - Energy perception motion significance target detection algorithm based on filter - Google Patents
Energy perception motion significance target detection algorithm based on filter Download PDFInfo
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Abstract
An energy perception motion significance target detection algorithm based on a filter is disclosed. The algorithm comprises the following steps of decoding video information to be observed into a YUV420 format of an independent image frame sequence, wherein a resolution ratio is consistent with an input video; setting a jump frame number to be 0 and reading in a current image frame F; through a motion characteristic and significant characteristic detection, acquiring a binarization image frame Fd after characteristic fusion; for an image Fd, carrying out horizontal direction and vertical direction energy search and energy threshold division calculating, and then carrying out denoising smoothing filtering processing respectively so as to acquire a final motion significance target area; according to the jump frame number, reading a next frame of image frame and taking the frame as input, carrying out looping execution on the step2, step3 and the step4 till that a final frame is read, terminating circulation and achieving an end. By using the algorithm of the invention, redundancy information and an error target can be effectively removed; an actual movement area of a motion significance target is calibrated; an initial significance area is prevented from manually selected; and a probability is provided for automatically realizing motion target tracking.
Description
Technical field
The invention belongs to motion well-marked target detection processing technology field, a kind of energy based on wave filter
Perception campaign well-marked target detection algorithm.
Background technology
The detection of motion well-marked target, as in computer vision field very important research topic, is supervised at video
The aspects such as control, Industry Control, robot vision and autonomous vehicle navigation are all with a wide range of applications.In target detection
In technology, along with application, being continually changing of applied environment, demand also becomes increasingly complex, accuracy, the reality to target detection
The requirement of Shi Xing, stability and portability is more and more higher.
At present, target is mainly positioned with Feature Fusion by target detection technique by feature detection, due to application
Environment is various, and the factor such as the choosing of feature, the complexity of detection algorithm and amalgamation mode all can produce shadow to object detection results
Ringing, the testing result after feature detection and fusion usually contains redundancy, and prior art cannot meet application to target detection
The performance requirement of technology.The approach generally improving target detection performance has two kinds: approach to be to start with from feature detection, spy
The when of levying extraction, choose more representative and feature targetedly, adapt to the multiformity of target, or optimize feature
The algorithm of detection technique, such as extracts multiple local feature and substitutes global characteristics, make the feature extracted more accurately express
Target property；Another approach is to start with from Feature Fusion mode, usually introduces fuzzy theory or grader cascade isotype is excellent
Change fusion results, to improve the degree of accuracy of target detection.For the former, owing to target is various, and affected by environmental change,
If Feature Selection is the most improper, the accuracy of target detection will be affected.For the latter, although the introducing of complicated algorithm
The accuracy of target detection can be improved, but algorithm complex can have a strong impact on the real-time of algorithm of target detection.
Filtering is the common technology of image procossing, is indispensable operation during Image semantic classification optimizes with anaphase,
Filter result directly influences picture quality and to the process of image and analysis.Conventional wave filter have nonlinear filter,
Median filter and Morphologic filters etc., these wave filter are mainly used in the noise reduction of image, smooth or shape recognition, edge inspection
The aspects such as survey.
Energy-aware wave filter used in the present invention, is with vertical by the level of any one frame in calculating video image
The summation of pixel energy, uses signal smoothing wave filter can effectively obtain motion well-marked target profile after processing energy
Region, thus substitute original manual type and choose the notable motion target area of vision or delimitation moving target initial motion region
Process.
Summary of the invention
Instant invention overcomes in existing target detection technique, there is redundancy or mistake in the testing result after feature detection and fusion
The problem of false information, it is provided that a kind of Energy-aware motion well-marked target detection algorithm based on wave filter, by the notable mesh that moves
Mark detection post-processing filter, more efficient, real-time target zone of action detection method more accurately.
By using complexity simple algorithm low, traditional to carry out feature detection and fusion, by testing result through the present invention
The Energy-aware motion well-marked target detection algorithm based on wave filter proposed processes, and removes mistake or redundancy object, highlights
Moving region scope, provides necessary pretreatment guarantee for the calculating of succeeding target central point, color with local shape factor scheduling algorithm.
So greatly strengthen effectiveness and the real-time of target detection technique,
In order to solve the technical problem of above-mentioned existence, the present invention is achieved by the following technical solutions:
A kind of Energy-aware motion well-marked target detection algorithm based on wave filter, this algorithm content specifically includes following step
Rapid:
The first step, is independent picture frame sequence by the video-information decoding to be observed of input, through colour space transformation
Becoming yuv space image, the resolution dimensions of this picture frame sequence keeps identical with original input video resolution；
Second step, by basic feature detection, Feature Fusion regular motion well-marked target detection technique, this uses light stream
Method extracts motion feature and marked feature with notable analytic process, uses adaptive weighted amalgamation mode, extracts in picture frame sequence
Target, and obtain the binary image frame information of moving target region, this information spinner will be by moving target region
Fixed point coordinate constitute；
3rd step, carries out energy search meter horizontally and vertically the most respectively to each frame in picture frame sequence
Calculating, remember that the size of video frame image to be measured is n × m, the energy of note horizontal direction the i-th row energy line is The energy of note vertical direction jth row energy line is
4th step, according to the relative distance between camera lens and tested motion well-marked target, pre-estimation moving target
Energy value scope, determine horizontal direction pre-estimation energy threshold PTHX, { PTHX∈Z|PTHX>=0} and vertical direction pre-estimation
Energy threshold PTHY, { PTHY∈Z|PTHY>=0}, horizontal direction pre-estimation energy threshold PTHXWith vertical direction pre-estimation energy threshold
PTHYDetermining according to the distance between dollying head mirror head and measured object, this distance can be by infrared sensor or laser sensor
Obtain；
5th step, to horizontal direction energy PX,And vertical direction
Energy PY,It is smoothed respectively obtaining smooth rear horizontal direction
Energy aggregationWith vertical direction energy aggregation
Wherein, smooth is smoothing processing wave filter, passes throughWithCommon factor part obtainSo that it is determined that motion
Summit, well-marked target zone boundary, demarcates motion well-marked target region.
Owing to using technique scheme, a kind of based on wave filter the Energy-aware motion well-marked target that the present invention provides
Detection algorithm, compared with prior art has such beneficial effect:
The degree of stability of video camera, mainly for static background, is required higher, it is impossible to the most very by existing target detection technique
It is applied to well dynamic background situation, affected by environment bigger.Meanwhile, existing optimized algorithm generally uses introducing grader and
The mechanism of habit improves accuracy, so considerably increases amount of calculation, reduces the real-time of detection, it is impossible to persistently follows the tracks of target, and
And be not easy to apply in the mini-plant of low-power consumption.
The present invention uses motion feature detection method to extract feature with marked feature analytic process, reduces computation complexity, carries
High autonomous power of test, reduces artificial participation.Under or uniform speed motion state static at photographic head, by by aforementioned two kinds of features from
Adapt to Weighted Fusion mode, efficiently separate target and background information, utilize Energy-aware wave filter can effectively remove redundancy
Information and false target, demarcate the actual activity region of motion well-marked target, it is thus achieved that object detection results more accurately, it is to avoid
The zone of action scope of the most selected artificial initial motion well-marked target, can be as the pretreatment skill of moving target automatic tracking
Art.
Owing to the present invention is in actual operation, mainly with image interframe luminance difference, image time-frequency domain conversation and energy
Perception search etc. is calculated as main, it is not necessary to carry out the complex calculation such as learning training, calculates process complexity low, it is simple to quickly obtain in time
Take motion well-marked target zone of action, sustainable tracking target.Less demanding to the kinestate of video camera itself, it is adaptable to take the photograph
Camera is static or the situation of uniform translation, uses in the indoor scene that illumination variation is the most violent, can rapid detection single, multiple
Moving target, meanwhile, to the kinestate of target without too many requirement, target at the uniform velocity, speed change and the situation of discontinuous fluid
Under, motion well-marked target zone of action can be accurately detected.The present invention can remove redundancy and mistake effectively
Target, demarcates the actual activity region of motion well-marked target, it is to avoid the most selected artificial initialization marking area, for being automatically obtained
Motion target tracking provides may.Real-time, computation complexity is low, it is possible to be efficiently applied to the power consumptions such as embedded, portable
Require strict mini-plant.
Accompanying drawing explanation
Fig. 1 is the design principle logic chart of Energy-aware wave filter；
Fig. 2 be video camera static time, single goal motion motion well-marked target detection result of implementation schematic diagram；
Fig. 3 be video camera static time, two target travels motion well-marked target detection result of implementation schematic diagram；
Fig. 4 be video camera static time, single goal variable motion motion well-marked target detection result of implementation schematic diagram；
When Fig. 5 is camera translation, the motion well-marked target detection result of implementation schematic diagram of single goal motion；
When Fig. 6 is camera translation, the motion well-marked target detection result of implementation schematic diagram of three target travels.
Detailed description of the invention
With detailed description of the invention, the present invention is described in further detail below in conjunction with the accompanying drawings:
A kind of Energy-aware motion well-marked target detection algorithm based on wave filter, the design of its Energy-aware wave filter is former
Reason logic chart as it is shown in figure 1, this algorithm to be embodied as step as follows:
1st step: by the independent image frame sequence that video-information decoding to be observed is YUV420 form, resolution regards with input
Frequency keeps consistent；
2nd step: set frame-skipping number as 0, reads in current image frame F；
3rd step: detected by motion feature and marked feature, obtain binary image frame F after Feature Fusiond；
4th step: to image Fd, carry out horizontally and vertically energy search, energy threshold and divide and calculate, then distinguish
Carry out denoising, the disposal of gentle filter, it is thus achieved that final motion well-marked target region
5th step: according to frame-skipping number, reads next frame picture frame and performs the 2nd step, the 3rd step, the 4th step as input, circulation,
Until having read the last frame of video, terminate circulation, it is achieved terminate.
Embodiment 1:
Video camera is static, single goal motion conditions
The present embodiment applies the present invention under video camera resting state, the motion well-marked target inspection of single target motion
Survey.With this understanding, video camera is mounted and fixed to certain robot or spider top, and level shoots, in the visual field of camera lens
In, a human target, according to the speed of 0.6m/s, draws near and enters into camera coverage.This video is mainly for indoor scene
Or the no motion of situation of shooting background, but, background comprises the indoor common furniture things such as window, desk, chair, chest
Product, with character costume, wear clothes unrelated, during shooting, there is not acute variation in illuminance, and it is micro-that the present embodiment is not related to night vision etc.
Light special environment.
Embodiment parameter declaration: video format avi, video frame number 15 frame, video image size 320 × 240.Pre-estimation threshold
Value PTHX=70, PTHY=15.
The present embodiment by arbitrary frame process as a example by, result as in figure 2 it is shown, Fig. 2-(1) is decoded input picture frame, warp
Cross motion feature detection and marked feature detects, respectively obtain motion feature binary picture and marked feature binary picture, such as figure
Shown in 2-(2) and 2-(3)；The binary image frame information of motion well-marked target region is obtained after self adaptation merges,
As shown in Fig. 2-(4)；Utilize Energy-aware filtering that binary image frame carries out horizontally and vertically energy search, energy
Amount threshold value divides and calculates, then carries out denoising smooth Filtering Processing respectively, and final acquisition motion well-marked target region, such as Fig. 2-(5)
Shown in.
Embodiment 2:
Video camera is static, two target travel situations
The present embodiment applies the present invention under video camera resting state, the inspection of the motion well-marked target of two target travels
Survey.With this understanding, video camera is mounted and fixed to certain robot or spider top, and level shoots, in the visual field of camera lens
In, two human target are respectively according to the speed of 0.6m/s and 0.8m/s, from the close-by examples to those far off away from camera direction.This video is main
For the no motion of situation of indoor scene or shooting background, but, background comprises the indoor such as window, desk, chair, chest
Common article of furniture, with character costume, wear clothes unrelated, during shooting, there is not acute variation in illuminance, and the present embodiment does not relates to
And the low-light special environment such as night vision.Embodiment parameter declaration: video format avi, video frame number 30 frame, video image size 320
×240.Pre-estimation threshold value PTHX=70, PTHY=15.
The present embodiment by arbitrary frame process as a example by, result as it is shown on figure 3, Fig. 3-(1) is decoded input picture frame, warp
Cross motion feature detection and marked feature detects, respectively obtain motion feature binary picture and marked feature binary picture, such as figure
Shown in 3-(2) and 3-(3)；The binary image frame information of motion well-marked target region is obtained after self adaptation merges,
As shown in Fig. 3-(4)；Utilize Energy-aware filtering that binary image frame carries out horizontally and vertically energy search, energy
Amount threshold value divides and calculates, then carries out denoising smooth Filtering Processing respectively, and final acquisition motion well-marked target region, such as Fig. 3-(5)
Shown in.
Embodiment 3:
Video camera is static, single goal variable motion situation
The present embodiment applies the present invention under video camera resting state, the motion well-marked target of single target variable motion
Detection.With this understanding, video camera is mounted and fixed to certain robot or spider top, and level shoots, regarding at camera lens
Field, single human target the most first moves according to 0.6m/s speed, and gradually speed change, moves with any direction.This video master
Will for the no motion of situation of indoor scene or shooting background, but, background comprises the rooms such as window, desk, chair, chest
In common article of furniture, with character costume, wear clothes unrelated, during shooting, there is not acute variation in illuminance, and the present embodiment is not
Relate to the low-light special environments such as night vision.
Embodiment parameter declaration: video format avi, video frame number 100 frame, video image size 320 × 240, pre-estimation
Threshold value PTHX=70, PTHY=15.
The present embodiment is as a example by arbitrary frame processes, and as shown in Figure 4, Fig. 4-(1) is decoded input picture frame to result, warp
Cross motion feature detection and marked feature detects, respectively obtain motion feature binary picture and marked feature binary picture, such as figure
Shown in 4-(2) and 4-(3)；The binary image frame information of motion well-marked target region is obtained after self adaptation merges,
As shown in Fig. 4-(4)；Utilize Energy-aware filtering that binary image frame carries out horizontally and vertically energy search, energy
Amount threshold value divides and calculates, then carries out denoising smooth Filtering Processing respectively, and final acquisition motion well-marked target region, such as Fig. 4-(5)
Shown in.
Embodiment 4:
Camera translation, single goal motion conditions
The present embodiment applies the present invention under video camera mobile status, the motion well-marked target inspection of single target motion
Survey.With this understanding, hand-held taked by video camera, translates with the speed constant level of 0.5m/s, outside the visual field of camera lens, and one
Human target, according to the speed of 0.6m/s, draws near and enters into camera coverage.This video mainly for video camera uniform translation,
The situation that background moves relative to camera lens, but, background comprises the indoor common furniture such as window, desk, chair, chest
Article, with character costume, wear clothes unrelated, during shooting, there is not acute variation in illuminance, and the present embodiment is not related to night vision etc.
Low-light special environment.
Embodiment parameter declaration: video format avi, video frame number 30 frame, video image size 320 × 240, pre-estimation threshold
Value PTHX=70, PTHY=15.
The present embodiment by arbitrary frame process as a example by, result as it is shown in figure 5, Fig. 5-(1) is decoded input picture frame, warp
Cross motion feature detection and marked feature detects, respectively obtain motion feature binary picture and marked feature binary picture, such as figure
Shown in 5-(2) and 5-(3)；The binary image frame information of motion well-marked target region is obtained after self adaptation merges,
As shown in Fig. 5-(4)；Utilize Energy-aware filtering that binary image frame carries out horizontally and vertically energy search, energy
Amount threshold value divides and calculates, then carries out denoising smooth Filtering Processing respectively, and final acquisition motion well-marked target region, such as Fig. 5-(5)
Shown in.
Embodiment 5:
Camera translation, three target travel situations
The present embodiment applies the present invention under video camera mobile status, the inspection of the motion well-marked target of three target travels
Survey.With this understanding, hand-held taked by video camera, with the speed uniform translation of 0.5m/s, outside the visual field of camera lens, and three personages
Target, according to the speed of 0.6m/s, 0.8m/s and 1.2m/s, keeps a direction motion.This video is mainly for video camera at the uniform velocity
Translation, background moves relative to camera lens and target is multiple situation, but, background comprises window, desk, chair,
The indoor common article of furniture such as chest, with character costume, wear clothes unrelated, during shooting, there is not acute variation in illuminance, this
Embodiment is not related to the low-light special environments such as night vision.
Embodiment parameter declaration: video format avi, video frame number 50 frame, video image size 320 × 240, pre-estimation threshold
Value PTHX=70, PTHY=15.
The present embodiment is as a example by arbitrary frame processes, and as shown in Figure 6, Fig. 6-(1) is decoded input picture frame to result, warp
Cross motion feature detection and marked feature detects, respectively obtain motion feature binary picture and marked feature binary picture, such as figure
Shown in 6-(2) and 6-(3)；The binary image frame information of motion well-marked target region is obtained after self adaptation merges,
As shown in Fig. 6-(4)；Utilize Energy-aware filtering that binary image frame carries out horizontally and vertically energy search, energy
Amount threshold value divides and calculates, then carries out denoising smooth Filtering Processing respectively, and final acquisition motion well-marked target region, such as Fig. 6-(5)
Shown in.
Claims (1)
1. an Energy-aware motion well-marked target detection algorithm based on wave filter, this algorithm content specifically includes following step
Rapid:
The first step, is independent picture frame sequence by the video-information decoding to be observed of input, becomes YUV through colour space transformation
Spatial image, the resolution dimensions of this picture frame sequence keeps identical with original input video resolution；
Second step, by basic feature detect, Feature Fusion regular motion well-marked target detection technique, this use optical flow method with
Notable analytic process extracts motion feature and marked feature, uses adaptive weighted amalgamation mode, extracts the mesh in picture frame sequence
Mark, and obtain the binary image frame information of moving target region, this information spinner will determining by moving target region
Point coordinates is constituted；
3rd step, carries out energy search horizontally and vertically the most respectively and calculates each frame in picture frame sequence,
The size remembering video frame image to be measured is n × m, and the energy of note horizontal direction the i-th row energy line is The energy of note vertical direction jth row energy line is
4th step, according to the relative distance between camera lens and tested motion well-marked target, the energy of pre-estimation moving target
Amount value scope, determines horizontal direction pre-estimation energy threshold PTHX, { PTHX∈Z|PTHX>=0} and vertical direction pre-estimation energy
Threshold value PTHY, { PTHY∈Z|PTHY>=0}, horizontal direction pre-estimation energy threshold PTHXWith vertical direction pre-estimation energy threshold PTHY
Determining according to the distance between dollying head mirror head and measured object, this distance can be obtained by infrared sensor or laser sensor
?；
5th step, to horizontal direction energy PX,With vertical direction energy
PY,It is smoothed respectively obtaining smooth rear horizontal direction energy
SetWith vertical direction energy aggregation
Wherein, smooth is smoothing processing wave filter, passes throughWithCommon factor part obtainSo that it is determined that motion is notable
Target area boundaries summit, demarcates motion well-marked target region.
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