CN101610408A - Video protection disorder method and structure - Google Patents
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Abstract
The invention discloses a kind of video protection disorder method and structure.This video protection disorder method reaches the purpose that privacy information such as people's face or other interesting target in the video is obtained in protection by with the area-of-interest scramble in the video scene, can be used for the communication of video monitoring system or Internet video.Video protection disorder method of the present invention mainly comprises three modules: video capture device, intellectual analysis processing unit, video scrambling coding module.Wherein, the intellectual analysis processing unit has adopted such as detection techniques such as the change-detection in the scene, the detections of people's face, to obtain people or the area-of-interest of target in scene in the video scene.Described video scrambling coding module is used for video content is carried out scrambling and coding.According to an importance of the present invention, interesting areas is by automatic scramble, and when the user was authorized to, video scene was recovered so that discern.In addition, described video protection disorder method can be controlled the scramble degree.
Description
Technical field
The present invention relates to the video monitoring technology, be meant video protection disorder method and structure in the video monitoring technology especially.
Background technology
Along with the increase of crime levels and threat, safety has become world's question of common concern.Video monitoring is one of method that addresses this problem.Except public safety, video monitoring also can solve some other problemses effectively, as the adjusting of crowded urban traffic amount, flow of the people.Large-scale for many years supervisory control system has obtained using widely in the main place such as airport, bank, highway or down town etc.
Because traditional video monitoring technology is generally artificial supervision, exist many deficiencies such as fatiguability, easily carelessness, reaction speed are slow, labour cost height.Therefore, people study the intelligent video monitoring technology of a kind of digitlization, standardization, intellectuality and IP networkization gradually in recent years.
Yet, when above-mentioned intelligent video monitoring system improves safety, brought another problem, i.e. the infringement of privacy.Because the scene of video monitoring system monitoring is often similar or belong to individual or privately owned, comprise a lot of privacy informations in the scene of monitoring, such as people, car or other interested target, and such as sending to by network in the process of far-end monitoring system, these privacy informations are disclosed unavoidably, and this has just produced the problem that privacy is invaded.
In fact, when being born from " electronic eyes ", the problem of the protection person of being monitored privacy has just occurred, and along with the increase of surveillance, this problem becomes more and more outstanding.
In sum, press for a kind of scheme that can solve contradiction between video monitoring and the privacy infringement at present, promptly propose a kind of secret protection scheme that can be used for video monitoring.
Summary of the invention
In view of this, main purpose of the present invention is to provide a kind of video protection disorder method and structure that is used for video monitoring system.Described video protection disorder method is protected the privacy in the video communication or is authorized anonymous part to reach by with interesting areas scramble in the video scene.Interesting areas can be an arbitrary shape, for example the position of people's face.
For achieving the above object, technical scheme of the present invention is achieved in that
According to an aspect of the present invention, the invention provides a video protection scramble structure that is used for video monitoring system, described video protection scramble structure comprises:
Video capture device is used to obtain video content;
The intellectual analysis processing unit is used to analyze described video content, to obtain interesting areas;
Video scrambling coding module is used for the described area-of-interest of scramble, and video content, so that Network Transmission.
Described video capture device comprises visible spectrum video camera, near-infrared video camera and thermal camera.Described near-infrared video camera and thermal camera allow to use under the low light level of no additional light rays.
Described intellectual analysis processing unit adopts target detection techniques such as the detection of people's face, car plate detection, can obtain target and location according to described detection technique, described intellectual analysis processing unit specifically comprises: moving target identification module, moving object classification module, motion target tracking module, moving target locking module and moving target extraction module.
Described video scrambling coding module comprises conversion module, scramble module and entropy coding module.
According to a further aspect in the invention, the invention provides a kind of video protection disorder method that utilizes described video protection scramble structure, this method comprises:
Steps A, obtain video information, obtain scene image, and send to the intellectual analysis processing unit by video capture device;
Step B, receive scene image by the intellectual analysis processing unit after, by intellectual analysis to scene image, each target is discerned, classifies, follows the tracks of, locked and extracts, obtaining the area-of-interest of target, and send it to video scrambling coding module; With
Step C, receive image behind the intellectual analysis by video scrambling coding module, the described area-of-interest of scramble, and video content are so that Network Transmission.
Obtain video content described in the steps A and realize that by video capture device this video capture device comprises visible spectrum video camera, near-infrared video camera and thermal camera.。Described near-infrared and thermal camera allow to use under the low light level of no additional light rays.
Analyzing video content described in the step B realizes by the intellectual analysis processing unit, be used for detecting and locating the target such as people's face, car of scene image, can realize that described intellectual analysis processing unit specifically comprises: moving target identification module, moving object classification module, motion target tracking module, moving target locking module and moving target extraction module by multiple detection and location technology.For example: " Human Faces in Video Frame.InternationalPublication No.WO 2006/070249 A1; 2006; 7; 6 and WO, 2006/006081 A2; 2006; 1,19 "; " H.A.Rowley, S.Baluja and Kanade.Neural network-BasedFace Detection.IEEE Trans.Pattern Analysis and Machine Intelligence, 1998, vol.20 (1) "; " M.H.Yang, D.Kriegman, and N.Ahuja.DetectingFaces in Images:A Survey.IEEE Trans.Pattern Analysis and MachineIntelligence, 2002, vol.24 (1) "; " Liu Yiguang, Shen Li. utilize Hausdorff apart from facial image location algorithm [J]. computer research and development, 2001, (04) "; " M.H.ter Brugge, J.h.Stevens, J.A.G.Nijhuits.License Plate Recognition Using DTCNNs[M] .Proceeding of the IEEE International Workshop on Cellular NeuralNetWorks and their Application, 1998 ".Wherein, described interesting areas is meant the locating area of the people's face, car plate and other target that obtain by multiple detection technique such as the detection of people's face, car plate detection.
The area-of-interest of scramble described in the step C realizes that by video scrambling coding module described video scrambling coding module comprises conversion module, scramble module and entropy coding module.Described scramble area-of-interest is used for the area-of-interest that obtains among the scramble video content step B.
Described step C mainly comprises three parts: conversion, scramble and entropy coding.According to the order difference of scramble, described step C mainly contains three kinds of scrambling and coding modes: before the coding in image area scramble, during coding in transform domain scramble, coding back scramble in code stream.
Before the described coding in image area scramble comprise:
1) scramble promptly carries out scramble to the significant bits plane that receives the pixel of area-of-interest in the image and handles;
2) conversion, the image that is about to after scramble is handled carries out the frequency domain transform processing, can realize by DCT or wavelet transformation;
3) entropy coding, the video after the scramble conversion soon carries out entropy coding, with output code flow, can realize by Huffman coding or arithmetic coding.
During described coding in transform domain scramble comprise:
1) conversion is promptly carried out the frequency domain transform processing to receiving image, can realize by DCT or wavelet transformation;
2) scramble is promptly selected the frequency coefficient of area-of-interest, and it is carried out scramble handle;
3) entropy coding, soon the video behind the conversion scramble carries out entropy coding, with output code flow, can realize by Huffman coding or arithmetic coding.
Described coding back scramble in code stream comprises:
1) conversion is promptly carried out the frequency domain transform processing to receiving image, can realize by DCT or wavelet transformation;
2) entropy coding, the video after the conversion soon carries out entropy coding, with output code flow, can realize by Huffman coding or arithmetic coding;
3) scramble is promptly selected the code stream of area-of-interest, and it is carried out scramble handle.
Disorder method among the described step C can be realized by image scrambling or watermarked two kinds of methods.
Described image scrambling method is meant by the position or the color of pixel of image " are upset ", thereby makes original image become a rambling new images, can realize by the mapping of the dimensional Logistic in the chaos algorithm.
Described Logistic mapping is a kind of dynamical system that very simply but is widely used, and it is defined as follows:
x
i+1＝μx
i(1-x
i)
Wherein, μ (0＜μ≤4) is called the branch parameter.When 0.5699456L＜μ≤4, the Logistic mapping is in chaos state, and works as x
iValue during ∈ (0,1) after the Logistic mapping also drops in (0,1) scope.
Described employing Logistic mapping realizes that image scrambling is meant that utilizing Logistic to shine upon produces at random not repetitive sequence, rearranges image according to this sequence then, and detailed process is as follows: in the chaotic region of Logistic mapping, choose an initial value x
0μ just can obtain a movement locus with the branch parameter, because this track is acyclic, so there are not two identical states in the whole track.We therefrom choose a finite length sequence arbitrarily, number to it by the position of numerical values recited in sequence of state, and then each state can obtain a unique numbering, and so just general's real number at random is converted into integer at random.The numbered sequence that said method obtains can be used to that image is carried out scramble and handles.
In the described image scrambling method, the initial value x of Logistic mapping
0, branch parameter μ and sequence length be as key.
Described watermarked method is meant that with described image be carrier, embeds noise sequence inside, thereby the image fault of making reaches the purpose of image scrambling.Described noise sequence can be the pseudo noise that is produced according to key value by pseudorandom generator, and described key value is meant the parameter of selecting at random, and pseudorandom generator can generate a series of pseudo noises according to above-mentioned parameter.
Described watermarked method can realize that the watermark embedding formula is by common open fire impression method:
f′＝f+α·w
Wherein, f is the frequency coefficient of described mark, and α is the embedment strength of watermark, and w is described noise sequence, and f ' is the frequency coefficient after watermarked.By regulating the value of α, the scramble degree or the distortion factor that can the control chart picture.
In the described watermarked method, the key value of generation noise sequence and embedment strength α are as key.
A further object of the present invention is to provide a kind of conditional access control technology, with target classification scrambles different in the video scene, and give different authorized users the key of using in the scramble by Network Transmission, authorized user can have the video content of the different distortion factors according to the cipher key access that has.
Described conditional access control technology is used the two-stage scramble: one side scramble interesting areas, corresponding first secret key encryption of key value; Scramble entire image on the other hand, corresponding key value is with second secret key encryption.Like this, the person of peeping can not access system in video data.In addition, the operator of supervisory control system is owing to have second key, can check that scene but can not discern existing people or target fully.In described system, have only the people who has two keys simultaneously under undistorted situation, to browse whole scene, comprise people's face or other interested target in the scene.
Video protection disorder method provided by the present invention and structure have following advantage and characteristics:
1) the intellectual analysis processing unit can detect each target in the video pictures automatically, and can automatically lock moving target in the picture, accurately follow the tracks of and locate, can ignore simultaneously the influence of the disturbing factors such as shade, rain, snow of animal, the branch that shakes, cloud.
2) video scrambling coding module has been carried out the scramble processing to video content, therefore has privacy protection function, can protect the privacy information that relates to effectively, comprises people, interested other target and scene.
3) the invention provides a kind of conditional access control technology, with target classification scrambles different in the video scene, and give different authorized users the key of using in the scramble by Network Transmission, authorized user can have the video content of different distortions according to the cipher key access that has.
Description of drawings
Fig. 1 is video protection scramble structural representation among the present invention;
Fig. 2 is video protection disorder method schematic flow sheet among the present invention;
Fig. 3 A for coding among the present invention before in image area the structural representation of scramble;
Fig. 3 B among the present invention during coding in transform domain the structural representation of scramble;
Fig. 3 C is the structural representation of coding back scramble in code stream among the present invention;
Fig. 4 is for having user's process chart of key at Fig. 3 B among the present invention;
Fig. 5 is not for there being user's process chart of key at Fig. 3 B among the present invention;
Embodiment
Core concept of the present invention is: at first obtain video content by a video capture device; Analyze described video content afterwards, to obtain interesting areas; The last described area-of-interest of scramble, and video content are so that Network Transmission.
Below, introduce embodiments of the present invention with reference to the accompanying drawings.
Figure 1 shows that video protection scramble structural representation among the present invention, comprising: video capture device 10 is used to obtain video content; Intellectual analysis processing unit 20 is used to analyze described video content, to obtain interesting areas; Video scrambling coding module 30 is used for the described area-of-interest of scramble, and video content, so that Network Transmission.
Described video capture device 10 can be a visible spectrum video camera, near-infrared video camera or thermal camera.Described near-infrared video camera and thermal camera allow to use under the low light level of no additional light rays.
Described intellectual analysis processing unit 20 comprises the plurality of target detection technique, for example people's face detects, car plate detects, can obtain target and location according to described detection technique, specifically comprise moving target identification module, moving object classification module, motion target tracking module, moving target locking module and moving target extraction module.
Described intellectual analysis processing unit 20 can carry out target detection.Target detection mainly is to detect those pixels that do not conform to background model in the present frame, just extracts the foreground target of present frame after they are linked up.This target detection is to realize by the algorithm of for example gauss hybrid models method, frame difference method and dynamic self-adapting Beijing calculus of finite differences and so on.
After detecting target, 20 pairs of targets of intellectual analysis processing unit are followed the tracks of.Target following is by setting up the corresponding relation between frame and the frame, carries out similitude then and lives relatively that template matches realizes, this target following for example is that the frame track algorithm by Kalman filter method, standard waits and realizes.
After having finished target detection and having followed the tracks of, intellectual analysis processing unit 20 can obtain basic data information such as the position, size, color, shape, speed, direction, movement locus of target, utilizes these information intelligent analysis and processing unit 20 automatically tracking target to be carried out type identification.Type identification is for example utilized SVMs, linear classifier to wait and is realized.
Described video scrambling coding module 30 comprises conversion module, scramble module and entropy coding module.
In conjunction with Fig. 1, video protection disorder method schematic flow sheet as shown in Figure 2, idiographic flow is as follows:
Step 201: obtain video information by video capture device 10, obtain scene image, and send to intellectual analysis processing unit 20;
Step 202: after intellectual analysis processing unit 20 receives scene image, by intellectual analysis to scene image, each target is detected, follows the tracks of, classifies and locatees, obtaining the area-of-interest of target, and send it to video scrambling coding module 30;
Step 203: video scrambling coding module 30 receives the image behind the intellectual analysis, and the described area-of-interest of scramble, and video content are so that Network Transmission.
The intellectual analysis of the processing unit of intellectual analysis described in the step 202 20, be used for detecting and locating people's face of scene image, targets such as car, use plurality of target to detect and location technology, for example: " Human Faces in Video Frame.International Publication No.WO2006/070249 A1; 2006; 7; 6 and WO, 2006/006081 A2; 2006; 1,19 "; " H.A.Rowley, S.Baluja and Kanade.Neural network-Based FaceDetection.IEEE Trans.Pattern Analysis and Machine Intelligence, 1998, vol.20 (1) "; " M.H.Yang, D.Kriegman, and N.Ahuj a.Detecting Faces inImages:A Survey.IEEE Trans.Pattern Analysis and Machine Intelligence, 2002, vol.24 (1) "; " Liu Yiguang, Shen Li. utilize Hausdorff apart from facial image location algorithm [J]. computer research and development, 2001, (04) ", " M.H.ter Brugge, J.h.Stevens, J.A.G.Nijhuits.License Plate Recognition Using DTCNNs[M] .Proceeding of the IEEE International Workshop on Cellular NeuralNetWorks and their Application, 1998 ".Wherein, described interesting areas is meant the locating area of the people's face, car plate and other target that obtain by multiple detection technique such as the detection of people's face, car plate detection.
According to the difference of scramble order, described step 203 mainly contains three kinds of scrambling and coding modes: before the coding in image area scramble, during coding in transform domain scramble, coding back scramble in code stream.
Before the described coding in image area scramble comprise as shown in Figure 3:
1) scramble promptly carries out scramble to the significant bits plane that receives the pixel of area-of-interest in the image and handles;
2) conversion, the image that is about to after scramble is handled carries out the frequency domain transform processing, can realize by DCT or wavelet transformation;
3) entropy coding, the video after the scramble conversion soon carries out entropy coding, with output code flow, can realize by Huffman coding or arithmetic coding.
During described coding in transform domain scramble comprise as shown in Figure 4:
1) conversion is promptly carried out the frequency domain transform processing to receiving image, can realize by DCT or wavelet transformation;
2) scramble is promptly selected the frequency coefficient of area-of-interest, and it is carried out scramble handle;
3) entropy coding, soon the video behind the conversion scramble carries out entropy coding, with output code flow, can realize by Huffman coding or arithmetic coding.
Described coding back scramble in code stream comprises as shown in Figure 5:
1) conversion is promptly carried out the frequency domain transform processing to receiving image, can realize by DCT or wavelet transformation;
2) entropy coding, the video after the conversion soon carries out entropy coding, with output code flow, can realize by Huffman coding or arithmetic coding;
3) scramble is promptly selected the code stream of area-of-interest, and it is carried out scramble handle.
Wherein, the disorder method in the described step 203 can be realized by image scrambling or watermarked two kinds of methods.
Described image scrambling method is meant by the position or the color of pixel of image " are upset ", thereby makes original image become a rambling new images, can realize by the mapping of the dimensional Logistic in the chaos algorithm.
Described Logistic mapping is a kind of dynamical system that very simply but is widely used, and it is defined as follows:
x
i+1＝μx
i(1-x
i)
Wherein, μ (0＜μ≤4) is called the branch parameter.When 0.5699456L＜μ≤4, the Logistic mapping is in chaos state, and works as x
iValue during ∈ (0,1) after the Logistic mapping also drops in (0,1) scope.
Described employing Logistic mapping realizes that image scrambling is meant that utilizing Logistic to shine upon produces at random not repetitive sequence, rearranges image according to this sequence then, and detailed process is as follows: in the chaotic region of Logistic mapping, choose an initial value x
0μ just can obtain a movement locus with the branch parameter, because this track is acyclic, so there are not two identical states in the whole track.We therefrom choose a finite sequence length arbitrarily, number to it by the position of numerical values recited in sequence of state, and then each state can obtain a unique numbering, and so just general's real number at random is converted into integer at random.The numbered sequence that said method obtains can be used to that image is carried out scramble and handles.
In the described image scrambling method, the initial value x of Logistic mapping
0, branch parameter μ, and sequence length as key.
Described watermarked method is meant that with described image be carrier, embeds noise sequence inside, thereby the image fault of making reaches the purpose of image scrambling.Described noise sequence can be the pseudo noise that is produced by pseudorandom generator.
Described watermarked method can realize that the watermark embedding formula is by common open fire impression method:
f′＝f+α·w
Wherein, f is the frequency coefficient of described mark, and α is the embedment strength of watermark, and w is described noise sequence, and f ' is the frequency coefficient after watermarked.By regulating the value of α, the scramble degree or the distortion factor that can the control chart picture.
In the described watermarked method, the key value of generation noise sequence, embedment strength α are as key.
According to embodiments of the present invention, provided different user deciphering coding/decoding method below at Fig. 3 B (when promptly encoding in transform domain scramble).
Figure 4 shows that the user's process chart that has key among the present invention at Fig. 3 B, step is as follows:
Step 401: video decode, the scramble code stream of input is decoded;
Step 402: the frequency coefficient unrest that is inverted, recover original frequency domain data;
Step 403: frequency coefficient is carried out inverse transformation, to recover original video scene image;
Step 404: video shows, promptly shows the video content that receives.
Wherein, being inverted described in the step 402 disorderly will be according to the disorder method of described step 203.Disorder method in the described step 203 is to realize by image scrambling or watermarked two kinds of methods, and the random method that therefore is inverted also is to be inverted disorderly or two kinds of methods realizations of extraction watermark by image.
The described image random method that is inverted is the inverse process of image scrambling method, and this method comprises:
1) key that has according to the user obtains the initial value x of dimensional Logistic mapping
0, branch parameter μ, and sequence length;
2) the initial value x that shines upon according to Logistic
0, branch parameter μ and sequence length obtain to have limit for length Logistic sequence of mapping, and according to this sequence obtain one corresponding position encoded;
3) position encoded area-of-interest in the image is carried out anti-sorting operation according to described, to recover initial data.
Described extraction water mark method is the inverse process of watermarked method, and this method comprises:
1) key that has according to the user obtains to produce key value, the embedment strength α of noise sequence;
2), utilize pseudo-random sequence generator to produce pseudo noise according to described key value;
3) remove noise according to extracting the watermark formula, this formula is:
f″＝f′-α·w
Wherein, f ' is the frequency coefficient of described area-of-interest, and α is an embedment strength, and w is described noise sequence, f " for extracting the frequency coefficient after the watermark, just removes the frequency coefficient behind the noise.
Figure 5 shows that the user's process chart that does not have key among the present invention at Fig. 3 B, step is as follows:
Step 501: video decode, the scramble code stream of input is decoded;
Step 502: frequency coefficient is carried out inverse transformation, to recover original video scene image;
Step 503: video shows, promptly shows the video content that receives.
According to embodiments of the present invention, described video protection disorder method uses a conditional access control technology to protect privacy.Consistent with conditional access control, described video protection disorder method can control chart as the distortion factor of detail section.Especially, it allows the part of every frame video content by scramble.Additionally, each different access level has different encryption keys.For example, detected people and other targets can be by scrambles in the Same Scene, and background is not by scramble.Scramble can be applied in the encoding block corresponding to area-of-interest selectively.In addition, by random, can control the distortion factor of protection image at different yardsticks or quantification stratification.Under supervisory control system, the target such as people, car can not be identified like this, but scene is still very clear.In order to protect people or the target in the scene, encryption key needs preserve under severe control, but the unrest that can selectively be inverted when authorizing, to guarantee identifier and target.
Described conditional access control technology is used the two-stage scramble: one side scramble interesting areas, corresponding first secret key encryption of key value; Scramble entire image on the other hand, corresponding key value is with second secret key encryption.Like this, the person of peeping can not access system in video data.In addition, the operator of supervisory control system is owing to have second key, can check that scene but can not discern existing people or target fully.In described system, have only the people who has two keys simultaneously under undistorted situation, to browse whole scene, comprise people's face or other interested target in the scene.
Introduce various functions and application below according to overall view monitoring equipment of the present invention.
1, moving target identification and classification
Intellectual analysis processing unit of the present invention comprises moving target identification module, moving object classification module, can discern the character and the classification of different target intelligently.After the basic data information of detection and extraction target, event checking module is carried out type identification to target, accurately distinguishes people, car, animal etc.
Moving target identification and classification can be applicable to the recognition of face field.After detection identifies human body, obtain the human body head photo, and judge according to biological characteristic whether it is the full face of people's face, if then compare with the face template of predefined detection target automatically, thereby identify its identity.
Moving target identification and classification also can be applicable to vehicle license identification field: after identifying target and being vehicle, judge type of vehicle automatically, and the identification license number.
2, motion target tracking, locking and extraction
The intellectual analysis processing unit comprises motion target tracking module, moving target locking module and moving target extraction module, determines position, the size of target, with the form lock onto target of prompting frame, and extracts the movement locus of target on the video that receives.
When occurring a plurality of qualified target in the video pictures, the intellectual analysis processing unit keeps comprising the tracking picture of target complete automatically, and shows the movement locus of each target.
3, secret protection
The video protection disorder method is receiver, video at first, and the intellectual analysis video content to obtain area-of-interest, carries out scrambling and coding to the area-of-interest that obtains then again, finally can export the code stream of scramble.Described video protection disorder method can be realized privacy protection function by the scramble area-of-interest, can be used in the video communication system such as video monitoring system.
Secret protection can be applicable to the protection of information such as people's face, car, animal, scene.Only when having access rights, (have key), could check relevant privacy information by deciphering; Otherwise, can only obtain the video content of distortion.
The above; being preferred embodiment of the present invention only, is not to be used to limit protection scope of the present invention, is to be understood that; the present invention is not limited to implementation as described herein, and these implementation purpose of description are to help those of skill in the art to put into practice the present invention.Any those of skill in the art are easy to be further improved without departing from the spirit and scope of the present invention and perfect, therefore the present invention only is subjected to the restriction of the content and the scope of claim of the present invention, and its intention contains all and is included in alternative and equivalent in the spirit and scope of the invention that is limited by claims.
Claims (20)
1, a kind of video protection scramble structure that is used for video monitoring system is characterized in that, described video protection scramble structure comprises:
Video capture device is used to obtain video content;
The intellectual analysis processing unit is used to analyze described video content, to obtain interesting areas; With
Video scrambling coding module is used for the described area-of-interest of scramble, and video content, so that Network Transmission.
2, video protection scramble structure according to claim 1; it is characterized in that; described video capture device comprises: visible spectrum video camera, near-infrared video camera and thermal camera, wherein, described near-infrared video camera and thermal camera allow to use under the low light level of no additional light rays.
3, video protection scramble structure according to claim 1; it is characterized in that described intellectual analysis processing unit comprises: moving target identification module, moving object classification module, motion target tracking module, moving target locking module and moving target extraction module.
4, video protection disorder method according to claim 1 is characterized in that, described video scrambling coding module comprises: conversion module, scramble module and entropy coding module.
5, a kind of video protection disorder method that utilizes as the described video protection scramble of claim 1～4 structure, described video protection disorder method comprises the steps:
Steps A, obtain video information, obtain scene image, and send to the intellectual analysis processing unit by video capture device;
Step B, receive scene image by the intellectual analysis processing unit after, by intellectual analysis to scene image, each target is discerned, classifies, follows the tracks of, locked and extracts, obtaining the area-of-interest of target, and send it to video scrambling coding module; With
Step C, receive image behind the intellectual analysis by video scrambling coding module, the described area-of-interest of scramble, and video content are so that Network Transmission.
6, video protection disorder method according to claim 5 is characterized in that, described video capture device comprises: visible spectrum video camera, near-infrared video camera and thermal camera; Described intellectual analysis processing unit comprises: moving target identification module, moving object classification module, motion target tracking module, moving target locking module and moving target extraction module; Described video scrambling coding module comprises: conversion module, scramble module and entropy coding module.
7, video protection disorder method according to claim 5 is characterized in that, described step C comprises: conversion, scramble and entropy coding.
8, according to claim 5 or 7 described video protection disorder methods, it is characterized in that the scrambling and coding mode of described step C comprises: before the coding in image area scramble, during coding in transform domain scramble and coding back scramble in code stream.
9, video protection disorder method according to claim 8 is characterized in that, before the described coding in image area scramble comprise:
(1) scramble carries out scramble to the significant bits plane that receives the pixel of area-of-interest in the image and handles;
(2) conversion is carried out frequency domain transform with the image after the scramble processing and is handled, and can realize by DCT or wavelet transformation;
(3) entropy coding carries out entropy coding with the video after the scramble conversion, with output code flow, realizes by Huffman coding or arithmetic coding.
10, video protection disorder method according to claim 8 is characterized in that, during described coding in transform domain scramble comprise:
(1) conversion is carried out the frequency domain transform processing to receiving image, can realize by DCT or wavelet transformation;
(2) scramble is selected the frequency coefficient of area-of-interest, and it is carried out scramble handle;
(3) entropy coding carries out entropy coding with the video behind the conversion scramble, with output code flow, realizes by Huffman coding or arithmetic coding.
11, video protection disorder method according to claim 8 is characterized in that, described coding back scramble in code stream comprises:
(1) conversion is carried out the frequency domain transform processing to receiving image, can realize by DCT or wavelet transformation;
(2) entropy coding carries out entropy coding with the video after the conversion, with output code flow, realizes by Huffman coding or arithmetic coding;
(3) scramble is selected the code stream of area-of-interest, and it is carried out scramble handle.
12, video protection disorder method according to claim 7 is characterized in that, the disorder method among the described step C is realized by image scrambling method or watermarked method.
13, video protection disorder method according to claim 12, it is characterized in that, described image scrambling method is meant by the position or the color of pixel of image " are upset ", make original image become a rambling new images, realize by the mapping of the dimensional Logistic in the chaos algorithm; Described Logistic mapping is defined as follows:
x
i+1＝μx
i(1-x
i)
Wherein, μ (0＜μ≤4) is called the branch parameter; When 0.5699456L＜μ≤4, the Logistic mapping is in chaos state, and works as x
iValue during ∈ (0,1) after the Logistic mapping also drops in (0,1) scope.
14, video protection disorder method according to claim 13 is characterized in that, adopts the Logistic mapping to realize that image scrambling is meant that utilizing Logistic to shine upon produces at random not repetitive sequence, rearranges the method for image then according to this sequence; Described method comprises:
In the chaotic region of Logistic mapping, choose an initial value x
0μ obtains a movement locus with the branch parameter;
Therefrom choose a finite sequence length arbitrarily, number to it by the position of numerical values recited in sequence of state, then each state can obtain a unique numbering, and so just general's real number at random is converted into integer at random;
Wherein, the numbered sequence that obtains by described method can be used to image is carried out the scramble processing.
15, video protection disorder method according to claim 14 is characterized in that, the initial value x of described Logistic mapping
0, branch parameter μ and sequence length be as key.
16, video protection disorder method according to claim 12 is characterized in that, described watermarked method is meant that with described image be carrier, embeds noise sequence inside, thereby the image fault of making reaches the purpose of image scrambling.
17, video protection disorder method according to claim 16; it is characterized in that; described noise sequence is the pseudo noise that is produced according to key value by pseudorandom generator; described key value is meant the parameter of selecting at random, and pseudorandom generator can generate a series of pseudo noises according to above-mentioned parameter.
18, video protection disorder method according to claim 16 is characterized in that, described watermarked method is to realize by the open fire impression method, and the watermark embedding formula is:
f′＝f+α·w
Wherein, f is the frequency coefficient of described mark, and α is the embedment strength of watermark, and w is described noise sequence, and f ' is the frequency coefficient after watermarked.
19, video protection disorder method according to claim 18 is characterized in that, by regulating the value of α, the scramble degree or the distortion factor of coming the control chart picture.
20, video protection disorder method according to claim 19 is characterized in that, the key value of described noise sequence and embedment strength α are as key.
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