CN103945228B - Video frame in copy move altering detecting methods based on space-time relationship - Google Patents

Abstract

The invention provides a kind of video frame in copy move altering detecting methods based on space-time relationship, which carries out NO emissions reduction process according to the method for building up of image gaussian pyramid to frame of video first, the temporal associativity and spatial correlation of monitor video content is recycled to distinguish adaptive setting time threshold value and peak threshold, filter out the suspicious frame pair that there may be that frame in copy move is distorted afterwards using phase place correlation and based on the detection method of Block- matching, and calculate the binary map of description tampered region position.Conclusive judgement is carried out to the packet of suspicious frame using time threshold finally.The present invention has larger minimizing in operation time than analogous algorithms, and enhances algorithm for the robustness of Gaussian noise.When tampered region being described using binary map, add the operation of morphologic filtering eliminate the interference that erroneous judgement point is brought with noise spot to a certain extent, improve the accuracy rate of detection.

Description

Video frame in copy-move altering detecting method based on space-time relationship

Technical field

The invention belongs to video tampering detection field, and in particular to a kind of video frame in copy- based on space-time relationship Move altering detecting methods.

Background technology

With developing rapidly for information technology, digital video is obtained in various fields and is extensively applied.That day by day popularized is high-quality Amount digital camera equipment, powerful Video editing software and a large amount of video sharing web sites for rising regard acquisition numeral Frequently, and which is carried out maliciously distorting and becomes more and more easier.In judicial evidence collection, the verity so that digital video is maliciously distorted It is difficult to be guaranteed with integrity.How to judge that a piece of digital video is distorted with the presence or absence of malice exactly, have become information The important research topic in security fields one.

At present, typical video to be distorted be divided into frame according to operation object and distort and distorted with interframe.Video frame in copy- It is to replicate the sport foreground in certain section of video sequence that move is distorted, and pastes other certain not overlapping of same video In section video sequence, to reach the purpose for changing video original meaning, belong to one kind that frame in is distorted.Digital video altering detecting method Two kinds of active detecting and passive detection can be divided into.The video tampering detection of early stage mostly is the mode of active detecting, this kind of method Depend on the pretreatment to video.Video distorts the statistical nature that passive detection algorithm relies solely on digital video itself, such as Quantizing noise, textural characteristics, motion vector dependency etc. are judging whether video is maliciously tampered.Due to without the need in advance to video Processed, passive detection method practicality is higher by contrast.

Find through the retrieval to prior art, Chinese patent literature CN101707711A, publication date is 2010.05.12, a kind of " the video sequence copy-move altering detecting methods based on compression domain " is described, is this process employs The content similarity of video GOP and kinematic similitude degree are usurped with the presence or absence of copy-move with detecting video sequence as judgement feature Change.The one of the method has the disadvantage greatly to distort for interframe and is detected, and frame in copy-move is distorted and does not detect energy Power.This causes a kind of robust and effectively frame in copy-move altering detecting method is urgently suggested.Existing usurp for frame in The algorithm for changing, is predominantly detected to be covered by same background and is distorted as foreground area, and be directed to what frame in copy-move was distorted Through the retrieval to existing document, detection algorithm, finds that only having W.Wang proposed, its method is using phase place coherent detection two Two interframe whether there is suspicious similar area, after primary election recycle the similarity of spatial domain to determine phase two suspicious frames Like area, the size of final reference area determines whether that there is frame in copy-move distorts, but the method amount of calculation is high, Fixed threshold is poor for applicability and has certain limitation to cause false alarm rate higher due to decision pattern.

Content of the invention

For defect of the prior art, the present invention proposes a kind of video frame in copy- based on space-time relationship Move altering detecting methods.The method carries out NO emissions reduction process first with the method for building up of gaussian pyramid to frame of video, then Using the adaptive given threshold of the temporal associativity and spatial correlation of monitor video content, finally using phase place correlation and base Judge that with the presence or absence of frame in copy-move distort two-by-two by interframe for video in the detection method of Block- matching, finally using time threshold Value carries out conclusive judgement again to the packet of suspicious frame.

According to a kind of video frame in copy-move altering detecting method based on space-time relationship that the present invention is provided, tool Body step includes：

The first step：Video to be detected and reference video is read in, video to be detected and reference video are solved respectively Each frame of video for frame of video and is converted to gray-scale maps by code, to form sequence of frames of video S to be measured respectively_d(i, j, t) and Reference video frame sequence S_r(i, j, t), 1≤i≤M, 1≤j≤N, 1≤t≤L, wherein, i is pixel row coordinate, and j is pixel Point range coordinate, time indexs of the t for frame of video, M are the image pixel number that often row includes, and N is the picture that image each column includes Vegetarian refreshments number, L are video totalframes；

Second step：To sequence of frames of video S to be measured_d(i, j, t) and reference video frame sequence S_r(i, j, t) is respectively according to building The mode of vertical gaussian pyramid carries out a NO emissions reduction computing, obtains the new sequence of frames of video S to be measured after NO emissions reduction_{d_new}(i, J, t) and reference video frame sequence S_{r_new}(i, j, t), then by sequence S_{d_new}(i, j, t) and S_{r_new}(i, j, t) is utilized respectively Background subtraction method obtains the video sequence S after removing time redundancy_{d_re}(i, j, t) and S_{r_re}(i,j,t)；And remove the time Reference video frame sequence after redundancy is made up of the multiple video sequences comprising sport foreground, and wherein, the time is superfluous Remaining, refer to the background frames not comprising sport foreground；

3rd step：To video sequence S_{r_re}(i, j, t), by adaptive threshold set algorithm, obtains time threshold T_thresholdWith phase place correlation peak threshold value P_threshold；

4th step：Using phase place correlation peak threshold value P_threshold, first to video sequence S_{d_re}(i, j, t) is calculated The phase place correlation peak of interframe, makes decisions to peak value two-by-two, and requires the absolute value of the difference of selected its time index of two frames It is more than time threshold T_threshold；If peak value exceedes phase place correlation peak threshold value P_threshold, then relative displacement is extracted, if relative Displacement is more than given threshold, then carry out the block level coupling of two suspicious interframe using the relative displacement, and otherwise two frame does not exist multiple Relation processed；Wherein, given threshold is referred to, m/12, and m is frame of video often row pixel sum；

5th step：The binary map for being marked with replication region position between two frames is obtained by block level coupling, to the binary map First expanded the morphologic filtering for corroding again, calculated the area in largest connected region in binary map after filtering, by the area with The area threshold of setting is compared, and determines that the two interframe domain of the existence is distorted, otherwise do not exist if more than threshold value；Wherein, The area threshold of the setting is proportional with original image area；

6th step：Repeat the 4th step, the 5th step until the satisfactory frame of video of all time index relations is through inspection Survey, that is, detected all frames of video to be measured；

7th step：Using time threshold T_threshold, it is grouped to there is the frame of video for replicating stickup relation, if point The video frame number at least having a certain group after group exceedes given threshold, then finally determine that the video sequence has frame in copy- Move is distorted, and is not otherwise existed.

Preferably, the second step includes procedure below：

Step A1：To every frame S (i, j, t in sequence of frames of video_k),t_k∈[1,l_new] carried out using Gassian low-pass filter template Filter in spatial domain smoothed after sequence of frames of video S_{_lowpass}(i,j,t_k), wherein, t_kFor the time index of video, l_newFor Video length；

Step A2：Sequence of frames of video S after to smoothing_{_lowpass}(i,j,t_k) interlacing is carried out every the down-sampled of row, adopt drop Video frame size after sample is reduced to a quarter of former frame of video, so just completes a NO emissions reduction computing；

Step A3：The sequence of frames of video after NO emissions reduction is read, and sequence of frames of video and background frames is obtained using background subtraction method Difference image sequence；

Step A4：To being corroded again and expansive working after difference image sequence binaryzation, by bianry image area of non-zero regions The area in domain judges that frame of video whether there is sport foreground；

Step A5：For sequence of frames of video S to be measured_{d_new}(i, j, t) directly chooses the composition of the frame of video containing sport foreground New sequence, and to reference video frame sequence S_{r_new}(i, j, t) also needs to divide the frame of video containing sport foreground according to labelling Section forms subsequence.

Preferably, the 3rd step includes procedure below：

Step B1：According to the reference video frame sequence S that segmentation is obtained_{r_new}(i, j, t), counts S_{r_new}(i, j, t) each cross-talk Length l of video sequence₁,l₂....l_N；

Step B2：, used as model is estimated, the value using following maximum likelihood moments estimation is as the time for selected quantum condition entropy Threshold value：

Wherein,For quantum condition entropy estimates of parameters, N is reference video total length；

Step C1：Reference video frame sequence S is obtained to segmentation_{r_new}(i, j, t), is partitioned into front scenery using background subtraction method Whether body, judge foreground object occupied area less than threshold value mn/48, and wherein, m is frame of video often row pixel sum, and n is video Frame each column pixel sum；The prospect for being only partitioned into negligible amounts is thought if less than threshold value, next execution step C2；

Step C2：Obtain reference video frame sequence S_{r_new}After sport foreground in (i, j, t) per cross-talk sequence, calculate respectively The average brightness in the sport foreground region of N number of subsequence；

Step C3：The sport foreground regional luminance meansigma methodss of all of subsequence are obtained μ₁,μ₂...μ_N, average in brightness Minimum and maximum mean flow rate μ is found in value sequence_max=max (μ₁,μ₂...μ_N),μ_min=min (μ₁,μ₂...μ_N)；

Step C4：After completing step C3, two groups and μ is obtained_max,μ_minThe corresponding subsequence of value, selectes two cross-talks respectively Certain frame in sequence is used as start frame, it is desirable to which the start frame includes the complete prospect for occurring first；

Step C5：Start frame is entered with subsequent frame the calculating of line phase correlation function successively, so, starting is utilized respectively Frame is calculated a series of corresponding respectively μ with subsequent frame_max,μ_minPhase place correlation function peak amplitudeAskMaximumAndMinima

Threshold value for ensureing to set has higher recall ratio, does following judgement：

IfThen

IfThen

λ₁, λ₂For the parameter for setting.

Preferably, the 4th step includes procedure below：

Step D1：The video sequence S of reading_{d_re}Two frame frame of video in (i, j, t) are designated as S respectively_{d_re}(i,j,t_k) and S_{d_re}(i,j,t_l), and | t_k-t_l| ＞ T_threshold, respectively to S_{d_re}(i,j,t_k) and S_{d_re}(i,j,t_l) FFT is carried out for frequency Rate figure S_{d_re}(u,v,t_k) and S_{d_re}(u,v,t_l)；

Step D2：Calculated by equation below and obtain frequency diagram S_{d_re}(u,v,t_k) and S_{d_re}(u,v,t_l) phase place related Scheme D (u, v), concrete formula is：

Wherein, * is represented and is taken conjugate operation to each element in matrix；

Step D3：Related for the phase place for obtaining figure D (u, v) is carried out image d (i, j) that IFFT inverse transformations obtain spatial domain, is tied Close correlation peak threshold value P_thresholdFind in spatial domain picture d (i, j) with the presence or absence of more than P_thresholdPeak point, if exist, Coordinate (the Δ that then record peak-peak is located_x,Δ_y), with upper left point as origin, if | Δ_x| ＞ m/12 and | Δ_y| ＞ m/12, Then proceed block level coupling, otherwise it is assumed that two frames for reading in do not have similar region；

Step E1：For S_{d_re}(i,j,t_k), by (Δ_x,Δ_y) as displacement, to S_{d_re}(i,j,t_k) do circulation shifting Dynamic process obtains new images

Step E2：WillAnd S_{d_re}(i,j,t_l) it is divided into 8 × 8 overlapping pixels block；Left with block of pixels The position that the coordinate representation block of pixels of upper angle pixel is located, calculatesAnd S_{d_re}(i,j,t_l) correspondence position pixel The similarity of block, if the luminance matrix of two block of pixels is respectively M₁(i,j),M₂(i, j), then calculate similarity using equation below ρ：

WhereinWithFor the meansigma methodss of two pixel Block Brightness, calculateAnd S_{d_re}(i,j,t_l) all right Answer the similarity of position block of pixels, if ρ more than set similarity threshold, then it is assumed that two block of pixels be identical, and The pixel value of corresponding position in binary map B (i, j) is set to 1；Otherwise, the pixel value of binary map corresponding position is set to 0； Wherein 1≤i≤M/2,1≤j≤N/2.Wherein, similarity threshold takes 0.99.

Preferably, the 7th step includes procedure below：

Step F1：If tampering detection algorithm detects m to there is the frame that copy-move is distorted, first according to frame when Between subscript sequential search is carried out to there is the frame that copy-move is distorted to m；When initial, searched with the value of time index successively Rope, the time index of first pair of tampering detection is stored in two arrays respectively；

Step F2：There is the frame that copy-move is distorted in sequential search second pair：

If second pair has two frames that copy-move is distorted, its time index is stored in array with above two respectively The absolute value of the difference of subscript time is respectively less than or is equal to α₁T_threshold, then by second pair exist frame that copy-move is distorted when Between subscript be stored in respectively before array in, wherein, α₁For adjusting thresholds coefficient；

If second pair of two time index that there is the frame that copy-move is distorted is stored under array with previous respectively The absolute value of the difference between timestamp is more than α₁T_threshold, then newly set up two arrays to deposit the time index of this pair of frames；

Next exist the time index of the frame pair that copy-move is distorted by with all of array that sets up before in deposit The time index of frame be compared, if be respectively less than to be equal to the time index absolute difference of element in all arrays before set Determine threshold value, be then deposited in the closest array of time domain；If absolute with the element time subscript in all arrays before Difference is all higher than given threshold, then newly set up two arrays to deposit the time index of this frame pair, until detecting to all M be grouped to there is the frame that copy-move is distorted；The time index number included in different arrays is designated as n respectively_i, i=1, 2,3,...；

Step F3：To the packet subscript number n for obtaining_iThe threshold alpha obtained with step F2₁T_thresholdCompared as follows：

Work as n_i≥α₁T_thresholdWhen, then it is assumed that there is frame in copy-move and distort in the video；

Work as n_i＜ α₁T_thresholdWhen, then it is assumed that there is no frame in copy-move and distort in the video.

A kind of video frame in copy-move altering detecting method and existing skill based on space-time relationship that the present invention is provided Art compares, with following obvious substance outstanding feature and remarkable advantage：

1. the method has carried out the pretreatment of a NO emissions reduction using the method for setting up Gauss pyramid to video sequence, this The process of sample on the premise of guarantee accuracy rate does not affect is greatly reduced operand and improves algorithm for additive Gaussian The robustness of noise.

2. the method using adaptive threshold value set mechanism, can according to different monitor video content characteristics to arrange when Between threshold value and phase place correlation peak threshold value, the two threshold values are the key parameters for being related to verification and measurement ratio and accuracy rate, compared to original The strategy of preset parameter in algorithm.The method has higher motility and more excellent Detection results.

3. the method performed morphologic filtering to the binary map of manipulation of record position before tampered region area is judged Operation, the operation made in binary map as noise and the erroneous point that causes of erroneous judgement are eliminated the accuracy that improve detection.

Description of the drawings

The detailed description that non-limiting example is made with reference to the following drawings by reading, the further feature of the present invention, Objects and advantages will become more apparent upon：

Fig. 1 is the overall flow schematic diagram that video frame in distorts passive detection algorithm；

Fig. 2 is phase place related operation and block level coupling idiographic flow schematic diagram；

Fig. 3 is overlapping block dividing method schematic diagram.

Specific embodiment

With reference to specific embodiment, the present invention is described in detail.Following examples will be helpful to the technology of this area Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that the ordinary skill to this area For personnel, without departing from the inventive concept of the premise, some deformations and improvement can also be made.These belong to the present invention Protection domain.

A kind of video frame in copy-move altering detecting method based on space-time relationship of the present invention, the method are main The method that is set up using gaussian pyramid is to video sequence NO emissions reduction, and the means using background subtraction remove the redundancy in video Content, is hereafter calculated using phase place correlation function and there may be the frame of video that region is distorted, and to suspicious frame of video to carrying out Block level is mated, and final packet judgement video whether there is to be distorted.Compared with prior art, the method have in operation time compared with Big minimizing, and algorithm is enhanced for the robustness of Gaussian noise.Compared with the algorithm of traditional fixed threshold, using self adaptation The time threshold and peak threshold that algorithm is obtained has more motility, for different types of video can show preferably performance. Moreover, the step of adding morphologic filtering before binary map calculates tampered region area can remove to a certain extent The interference brought with noise spot by erroneous judgement point, improves the accuracy rate of detection.

It is that sport foreground in just certain section video sequence is replicated that video frame in copy-move is distorted, and pastes In other certain section of video sequences not overlapped of same video, means are distorted to reach the one kind for the purpose for changing video original meaning, Belong to one kind that frame in is distorted.

The present invention is achieved by the following technical solutions, first to decompression after reference video and video to be detected carry out The NO emissions reduction of gaussian pyramid is processed.Reference video after using process obtains adaptive time threshold and phase place phase Close peak threshold.Again to process after video to be detected in frame calculate phase place correlation function two-by-two, if exist peak value and its Amplitude then records peak more than peak threshold and carries out block level coupling, then carries out shape to the binary map obtained after block level coupling State is filtered, the binary map maximum non-zero area after statistical filtering, is recognized if maximum non-zero area is more than the area threshold for setting There is distorting for frame in copy-move for two interframe, and keep a record, otherwise there is no the relation of distorting.There is frame in all The frame that copy-move is distorted is grouped, per group of frame number for including after statistical packet, time threshold after frame number exceedes adjustment When finally judge that the copy-move that the video has frame in is distorted.

Video frame in distorts the overall flow of passive detection algorithm as shown in Figure 1.Below with resolution as 360 × 288, Compressed format is wmv, and frame per second is 25fps, and totalframes is the reference of the video sequence to be measured and totalframes of 520 frames more than 520 Video is tested.

The first step：Read in video to be detected and reference video, using matlab in mmreader decode it for The frame of video of bmp forms is simultaneously converted into gray-scale maps using rgb2gray, respectively formation sequence S_d(i, j, t) and S_r(i,j, T) to carry out subsequent treatment, wherein 1≤i≤360,1≤j≤288,1≤t≤520, i are pixel row coordinate, and j is pixel Point range coordinate, time indexs of the t for frame of video；

Second step：To decoded sequence of frames of video S to be measured_d(i, j, t) and reference video frame sequence S_r(i, j, t) is pressed A NO emissions reduction computing is carried out according to the mode for setting up gaussian pyramid.New video sequences S after NO emissions reduction_{d_new}(i, j, t) and S_{r_new}(i, j, t), wherein 1≤i≤180,1≤j≤144,1≤t≤520 are obtained using background subtraction method and remove time redundancy Video sequence S after (i.e. totally stationary frame)_{d_re}(i, j, t) and S_{r_re}(i, j, t), wherein 1≤i≤180,1≤j≤ 144,1≤t≤l_{_new}, it is clear that l_{_new}≤520.And S_{r_re}(i, j, t) is by multiple video sequences S comprising sport foreground₁ (x,y,t)S₂(x,y,t)...S_N(x, y, t) is constituted.

Described video sequence is carried out a NO emissions reduction computing according to the mode for setting up gaussian pyramid and is subtracted using background Division obtains the video sequence concrete steps of removing time redundancy and refers to：

Step A1：To every frame S (i, j, t in video sequence_k),t_k∈[1,l_new] using size be 3 × 3, standard deviation is 1 Gassian low-pass filter template h (i, j), carries out frame of video S after filter in spatial domain is smoothed_{_lowpass}(i,j,t_k)=S (i, j, t_k) * h (i, j), wherein, (*) it is two-dimensional convolution computing.

Step A2：To smooth after video sequence carry out interlacing every row down-sampled, make down-sampled after frame of video chi The very little a quarter for being reduced to former frame of video, so just completes a NO emissions reduction computing.

Step A3：Read smooth rear pending frame of video, it is assumed that with t₁Moment frame as initial background frames f (i, j, t₁) (it is the frame of video only containing background that can manually select the first frame), by itself and t₁Moment frame of video S (i, j, t₁) make the difference.Differed from Partial image D (i, j, t₁)=| S (i, j, t₁)-f(i,j,t₁)|.

Step A4：To being corroded again and expansive working after difference image binaryzation, the disk mould that width is 5 is selected respectively Plate and width are that 8 disc template is carried out, and the non-zero pixels number of the bianry image after statistical disposition, and number is more than mn/ 48 (m is frame of video often row pixel sum, and n is frame of video each column pixel sum) think that video has sport foreground and to which Making marks, otherwise being judged as background frames, and background frames renewal is carried out using equation below, more new formula is：

F (i, j, t after renewal₂)=(1- α) f (i, j, t₂)+αf(i,j,t₁)

Wherein α be context update speed, f (i, j, t₂) it is t₂Moment frame.

Step A5：For video S to be measured_{d_new}(i, j, t) directly chooses the frame of video containing sport foreground and constitutes new sequence , and to reference video S_{r_new}(i, j, t) also needs to do following process according to labelling：Judging that present frame is the frame comprising prospect Afterwards, whether the former frame for checking present frame is the frame comprising prospect, if the frame comprising prospect, then adds present frame previous In sequence belonging to frame.If it is not, then restarting to set up one section of sequence, and continue the situation of calculated for subsequent frame.To whole section Video carries out above-mentioned process, can be by reference video S_{r_new}(i, j, t) inner video signal process comprising sport foreground out, is obtained Multiple video sequence S comprising sport foreground_{r_new1}(i,j,t)S_{r_new2}(i,j,t)...S_{r_newN}(i,j,t).

3rd step：Reference video frame sequence S after to process_{r_re}(i, j, t), by adaptive threshold set algorithm, obtains Arrive time threshold T_thresholdWith phase place correlation peak threshold value P_threshold.

Described auto-adaptive time threshold setting algorithm is mainly included the following steps that：

Step B1：Video sequence S of the reference video obtained according to step 2 segmentation_{r_new1}(i,j,t)S_{r_new2}(i,j, t)...S_{r_newN}(i, j, t), counts length l of each cross-talk video sequence₁,l₂....l_N.

Step B2：A kind of probability Distribution Model is selected for different video types, using probability Distribution Model and before The time samples of acquisition carry out parameter estimation, and try to achieve the average of sample, select quantum condition entropy here as estimating model, profit Value with maximum likelihood moments estimation the following is used as time threshold：

Wherein,For quantum condition entropy estimates of parameters, N is reference video total length；

The estimated value is just as time threshold T_threshold.When tampering detection is carried out, when time interval is more than above-mentioned threshold value Frame just enter the calculating of line phase correlation function.This is because, logically identical prospect will not be placed by interpolater In the video sequence in the same time period.

Described self adaptation phase place correlation peak threshold setting algorithm is mainly included the following steps that：

Step C1：In step 2, segmentation obtains video sequence S of reference video_{r_new1}(i,j,t)S_{r_new2}(i,j, t)...S_{r_newN}(i,j,t).This algorithm only considers the situation for having minority prospect simple motion.Using the background subtraction in step 2 Whether method is partitioned into foreground object, judge foreground object occupied area less than threshold value mn/48.Then think only to be partitioned into less than threshold value The prospect of negligible amounts, meeting the condition then carries out below step.

Step C2：After obtaining the sport foreground per cross-talk sequence, the sport foreground region of N number of video sequence is calculated respectively Average brightness, such as：The sport foreground regional luminance average value mu that k-th subsequence is calculated using equation below_k：

D_tFor the region that kth cross-talk sequence t frames have prospect, l_kFor the frame number that k-th sub-series of packets contains.

Step C3：The sport foreground regional luminance meansigma methodss of all of subsequence are obtained μ₁,μ₂...μ_N.Average in brightness Minimum and maximum mean flow rate μ is found in value sequence_max=max (μ₁,μ₂...μ_N),μ_min=min (μ₁,μ₂...μ_N).

Step C4:After completing step C3, two groups and μ is obtained_max,μ_minThe corresponding video sequence of value, is designated as S respectively_max (x, y, t), S_min(x, y, t), the length of video-frequency band are calculated as l respectively_max, l_min.This two sections of video sequences contain whole section respectively There is in reference video higher average brightness value and relatively low average brightness value sport foreground.To S_max(x, y, t), S_min(x,y,t) S in artificial selected video sequence_max(x,y,t_k), t_k∈[1,l_max] and S_min(x,y,t_l), t_l∈[1,l_min] as starting Frame, it is desirable to which the start frame includes the complete prospect for occurring first.

Step C5：By S_max(x,y,t_k) and S_min(x,y,t_l) enter the calculating of line phase correlation function with subsequent frame successively. So, sequence S_max(x, y, t), S_min(x, y, t) is utilized respectively start frame, and to be calculated a series of phase place to subsequent frame related The peak amplitude of functionTwo group phase place correlation functions are sought respectively Maximum and minima：

Threshold value for ensureing to set has higher recall ratio, does following judgement：

IfThen

IfThenParameter lambda is typically taken₁=1.4, λ₂=1.1.

4th step：Phase place correlation peak threshold value P obtained using step 3_threshold, first to new video sequence to be measured S_{d_re}(i, j, k) calculates the phase place correlation peak of interframe two-by-two, and peak value is made decisions, it is desirable to selected its time index of two frames Difference absolute value be more than time threshold T_threshold.If peak value exceedes given threshold, relative displacement (Δ can be extracted_x, Δ_y), if | Δ_x| ＞ m/12 and | Δ_y| ＞ m/12, then proceed block level coupling, otherwise there is no replication relation in two frame. This is because peak value occurs in the phase place correlation function meeting at the origin of identical image, the object that some original places are hovered needs to disappear with this Except which disturbs.

Described phase place related algorithm concrete steps refer to (accompanying drawing 2)：

Step D1：Assume that the two frame frame of video that reads in are designated as S respectively_{d_re}(i,j,t_k) and S_{d_re}(i,j,t_l), and time difference |t_k-t_l| ＞ T_threshold, FFT is carried out for frequency diagram S to which respectively_{d_re}(u,v,t_k) and S_{d_re}(u,v,t_l).

Step D2：The phase place correlation figure that can obtain two frames is calculated by equation below, and concrete formula is：

Wherein, * is to take conjugation to each element in matrix.

Step D3:Related for the phase place for obtaining figure D (u, v) is carried out image d (i, j) that IFFT inverse transformations obtain spatial domain, is tied Close correlation peak threshold value P that step 3 is obtained_thresholdFind in spatial domain picture d (i, j) with the presence or absence of more than P_thresholdPeak value Point, if existing, records the coordinate (Δ that peak-peak is located_x,Δ_y) (with upper left point as origin), if | Δ_x| ＞ m/12 and | Δ_y| ＞ m/12, then proceed block level coupling, otherwise it is assumed that two frames for reading in do not have similar region.Described block level coupling Concrete steps refer to：

Step E1：One of two frames optionally to be matched, it is assumed herein that select S_{d_re}(i,j,t_k).By (Δ_x,Δ_y) make For displacement, using the dip-image function pairs in matlab Digital Image Processing tool kits, which does loopy moving process and obtains Obtain new images

Step E2：WillAnd S_{d_re}(i,j,t_l) it is divided into 8 × 8 overlapping pixels block (accompanying drawing 3).With picture The position that the coordinate representation block of pixels of plain block top left corner pixel point is located, calculatesAnd S_{d_re}(i,j,t_l) corresponding position The similarity of block of pixels is put, if two block of pixels are respectively M₁(i,j),M₂(i, j), then calculate similarity using equation below：

WhereinWithFor the meansigma methodss of two pixel Block Brightness, calculateAnd S_{d_re}(i,j,t_l) all right The similarity of position block of pixels is answered, if ρ is more than the similarity threshold (being traditionally arranged to be 0.99) for setting, then it is assumed that two block of pixels It is identical, and the pixel value by correspondence position in binary map B (i, j) (coordinate position of block of pixels top left corner pixel) place It is set to 1.Otherwise, the pixel value of binary map corresponding position is set to 0.Wherein 1≤i≤180,1≤j≤144.

5th step：Binary map B (i, j) for being marked with tampered region position between two frames is obtained through block level coupling.To this Binary map is first expanded the morphologic filtering for corroding again, selects the disc template that width is 5 and the disk that width is 8 respectively Template is carried out.The maximum area of connected region in binary map is calculated after the completion of filtering, by the area and the area threshold for setting S_threshold=mn/48 is compared, and determines that the two interframe domain of the existence is distorted, otherwise do not exist if more than threshold value.

6th step：Repeat the 4th step, the 5th step until the satisfactory frame of video of all time index relations is through inspection Survey, that is, detected all frames of video to be measured.

7th step：Using time threshold T_threshold, it is grouped to there is the frame of video for replicating stickup relation, if point The video frame number at least having a certain group after group exceedes given threshold α₁T_threshold, then finally determine that the video sequence has frame Interior copy-move is distorted, and is not otherwise existed.

Described utilization time threshold carries out packet to the frame of video that there is duplication stickup relation and comprises the concrete steps that：

Step F1：If tampering detection algorithm detects m to there is the frame that copy-move is distorted.First according to frame when Between subscript sequential search is carried out to there is the frame that copy-move is distorted to m.When initial, with the value of time index, (this is to examine successively Consider the time continuity of motion) scan for, the time index t that there is the frame that copy-move is distorted by first couple₁And t₁+Δ t₁Array x is stored in respectively₁[n],x₂In [n].

Step F2：Next, there is the frame that copy-move is distorted in sequential search second pair again：

If second pair has two frames that copy-move is distorted, its time index t₂And t₂+Δt₂Respectively with above two It is stored in the absolute value of the difference of the subscript time of array | t₁-t₂| and | t₁-t₂+Δt₁-Δt₂| respectively less than or equal to α₁T_threshold, Array x before then be stored in the time index that second pair has the frame that copy-move is distorted respectively₁[n],x₂In [n].

If second pair of two time index that there is the frame that copy-move is distorted is stored under array with previous respectively The absolute value of the difference between timestamp | t₁-t₂| and | t₁-t₂+Δt₁-Δt₂| more than α₁T_threshold, then two arrays x are newly set up₃[n], x₄[n] is depositing the time index of this pair of frames.

Next exist the time index of the frame pair that copy-move is distorted by with all of array that sets up before in deposit The time index of frame be compared, and carry out and identical operation be described above.Until to all m for detecting to exist The frame that copy-move is distorted is grouped.Multipair array can be obtained.Different arrays x_i[n], i=1,2,3 ... in include Time index number is designated as n respectively_i, i=1,2,3 ....

Step F3：To the packet subscript number n for obtaining_iThe threshold value obtained with step F2 is compared as follows：

Work as n_i≥α₁T_thresholdWhen, we claim the video to there is frame in copy-move to distort.

Work as n_i＜ α₁T_thresholdWhen, we claim the video to there is no frame in copy-move to distort.If algorithm has n time by mistake Inspection, and n ＞ α₂N ought wherein λ ∈ [0,1], we claim tampering detection algorithm to there is flase drop to the video.

Generally α₁=0.7, α₂=0.2.α₂Referred to as flase drop is spaced regulation coefficient.

Above the specific embodiment of the present invention is described.It is to be appreciated that the invention is not limited in above-mentioned Particular implementation, those skilled in the art can make various modifications or modification within the scope of the claims, this not shadow Ring the flesh and blood of the present invention.

Claims (4)

1. a kind of video frame in copy-move altering detecting method based on space-time relationship, it is characterised in that concrete steps bag Include：

The first step：Video to be detected and reference video is read in, video to be detected and reference video are decoded as respectively Frame of video and each frame of video is converted to gray-scale maps, to form sequence of frames of video S to be measured respectively_d(i, j, t) and reference Sequence of frames of video S_r(i, j, t), 1≤i≤M, 1≤j≤N, 1≤t≤L, wherein, i is pixel row coordinate, and j is pixel point range Coordinate, time indexs of the t for frame of video, M are the image pixel number that often row includes, and N is the pixel that image each column includes Number, L are video totalframes；

Second step：To sequence of frames of video S to be measured_d(i, j, t) and reference video frame sequence S_r(i, j, t) is high according to setting up respectively This pyramidal mode carries out a NO emissions reduction computing, obtains the new sequence of frames of video S to be measured after NO emissions reduction_{d_new}(i,j,t) And reference video frame sequence S_{r_new}(i, j, t), then by sequence S_{d_new}(i, j, t) and S_{r_new}(i, j, t) is utilized respectively background Relief method obtains the video sequence S after removing time redundancy_{d_re}(i, j, t) and S_{r_re}(i,j,t)；And remove time redundancy Reference video frame sequence afterwards is made up of the multiple video sequences comprising sport foreground, and wherein, the time redundancy is Refer to the background frames not comprising sport foreground；

3rd step：To video sequence S_{r_re}(i, j, t), by adaptive threshold set algorithm, obtains time threshold T_thresholdWith Phase place correlation peak threshold value P_threshold；

4th step：Using phase place correlation peak threshold value P_threshold, first to video sequence S_{d_re}(i, j, t) calculates frame two-by-two Between phase place correlation peak, when making decisions to peak value, and requiring that the absolute value of the difference of selected its time index of two frames is more than Between threshold value T_threshold；If peak value exceedes phase place correlation peak threshold value P_threshold, then relative displacement is extracted, if relative displacement is big In given threshold, then the block level coupling of two suspicious interframe is carried out using the relative displacement, otherwise two frame does not have replication relation； Wherein, given threshold is referred to, m/12, and m is frame of video often row pixel sum；

5th step：The binary map for being marked with replication region position between two frames is obtained by block level coupling, the binary map is carried out The morphologic filtering for corroding again is first expanded, the area in largest connected region in binary map after filtering is calculated, by the area and setting Area threshold be compared, if more than determining that the two interframe domain of the existence is distorted if area threshold, otherwise do not exist；

6th step：Repeat the 4th step, the 5th step until the satisfactory frame of video of all time index relations is through detecting, i.e., All frames of video to be measured are detected；

7th step：Using time threshold T_threshold, it is grouped to there is the frame of video for replicating stickup relation, if after packet The video frame number at least having a certain group exceedes frame number threshold value, then finally determine that the video sequence has frame in copy-move and usurps Change, otherwise do not exist；

The second step includes procedure below：

Step A1：To every frame S (i, j, t in sequence of frames of video_k),t_k∈[1,l_new] space is carried out using Gassian low-pass filter template Domain filters the sequence of frames of video S after being smoothed_{_lowpass}(i,j,t_k), wherein, t_kFor the time index of video, l_newFor video Length；

Step A2：Sequence of frames of video S after to smoothing_{_lowpass}(i,j,t_k) carry out interlacing every row down-sampled, make down-sampled it Video frame size afterwards is reduced to a quarter of former frame of video, so just completes a NO emissions reduction computing；

Step A3：The sequence of frames of video after NO emissions reduction is read, the difference for sequence of frames of video and background frames being obtained using background subtraction method Partial image sequence；

Step A4：To being corroded again and expansive working after difference image sequence binaryzation, by bianry image non-zero region Area judges that frame of video whether there is sport foreground；

Step A5：For sequence of frames of video S to be measured_{d_new}(i, j, t) directly chooses the frame of video containing sport foreground and constitutes new sequence Row, and to reference video frame sequence S_{r_new}(i, j, t) is also needed the frame of video segmentation shape containing sport foreground according to labelling Into subsequence.

2. the video frame in copy-move altering detecting method based on space-time relationship according to claim 1, its feature It is, the 3rd step includes procedure below：

Step B1：According to the reference video frame sequence S that segmentation is obtained_{r_new}(i, j, t), counts S_{r_new}(i, j, t) each cross-talk video Length l of sequence₁,l₂....l_N；

Step B2：, used as model is estimated, the value using following maximum likelihood moments estimation is as time threshold for selected quantum condition entropy：

$T_{threshold}=\frac{1}{\stackrel{\‾}{\mathrm{\λ}}}=\frac{1}{N}\underset{k=1}{\overset{N}{\Σ}}{l}_k$

Wherein,For quantum condition entropy estimates of parameters, N is reference video total length；

Step C1：Reference video frame sequence S is obtained to segmentation_{r_new}(i, j, t), is partitioned into foreground object using background subtraction method, Whether foreground object occupied area is judged less than threshold value mn/48, wherein, m is frame of video often row pixel sum, and n is frame of video Each column pixel sum；The prospect for being only partitioned into negligible amounts is thought if less than threshold value, next execution step C2；

Step C2：Obtain reference video frame sequence S_{r_new}After sport foreground in (i, j, t) per cross-talk sequence, calculate respectively N number of The average brightness in the sport foreground region of subsequence；

Step C3：The sport foreground regional luminance meansigma methodss of all of subsequence are obtained μ₁,μ₂...μ_N, in average brightness sequence Minimum and maximum mean flow rate μ is found in row_max=max (μ₁,μ₂...μ_N),μ_min=min (μ₁,μ₂...μ_N)；

Step C4：After completing step C3, two groups and μ is obtained_max,μ_minThe corresponding subsequence of value, selectes two cross-talk sequences respectively In certain frame as start frame, it is desirable to the start frame includes the complete first prospect for occurring；

Step C5：Start frame is entered successively the calculating of line phase correlation function with subsequent frame, so, be utilized respectively start frame with Subsequent frame be calculated a series of respectively correspond to μ_max,μ_minPhase place correlation function peak amplitudeAskMaximumAndMinima

${\mathrm{\γ}}_{p_{max}}=max({\mathrm{\γ}}_{p_{max}1},{\mathrm{\γ}}_{p_{max}2},...{\mathrm{\γ}}_{p_{max}{l}_{max}}),{\mathrm{\γ}}_{p_{min}}=min({\mathrm{\γ}}_{p_{min}1},{\mathrm{\γ}}_{p_{min}2},...{\mathrm{\γ}}_{p_{min}{l}_{min}})$

Threshold value for ensureing to set has higher recall ratio, does following judgement：

IfThen

IfThen

λ₁, λ₂For the parameter for setting.

3. the video frame in copy-move altering detecting method based on space-time relationship according to claim 1, its feature It is, the 4th step includes procedure below：

Step D1：The video sequence S of reading_{d_re}Two frame frame of video in (i, j, t) are designated as S respectively_{d_re}(i,j,t_k) and S_{d_re}(i, j,t_l), and | t_k-t_l| ＞ T_threshold, respectively to S_{d_re}(i,j,t_k) and S_{d_re}(i,j,t_l) FFT is carried out for frequency diagram S_{d_re} (u,v,t_k) and S_{d_re}(u,v,t_l)；

Step D2：Calculated by equation below and obtain frequency diagram S_{d_re}(u,v,t_k) and S_{d_re}(u,v,t_l) the related figure D of phase place (u, V), concrete formula is：

$D(u,v)=\frac{S_{d\_re}(u,v,t_k)S_{d\_re}{(u,v,t_l)}^{*}}{\left|S_{d\_re}(u,v,t_k)S_{d\_re}{(u,v,t_l)}^{*}\right|}$

Wherein, * is represented and is taken conjugate operation to each element in matrix；

Step D3：Related for the phase place for obtaining figure D (u, v) is carried out image d (i, j) that IFFT inverse transformations obtain spatial domain, in conjunction with phase Close peak threshold P_thresholdFind in spatial domain picture d (i, j) with the presence or absence of more than P_thresholdPeak point, if exist, remember Coordinate (the Δ that record peak-peak is located_x,Δ_y), with upper left point as origin, if | Δ_x| ＞ m/12 and | Δ_y| ＞ m/12, then after Continuing carries out block level coupling, otherwise it is assumed that two frames for reading in do not have similar region；

Step E1：For S_{d_re}(i,j,t_k), by (Δ_x,Δ_y) as displacement, to S_{d_re}(i,j,t_k) do at loopy moving Reason obtains new images

Step E2：WillAnd S_{d_re}(i,j,t_l) it is divided into 8 × 8 overlapping pixels block；With block of pixels upper left corner picture The position that the coordinate representation block of pixels of vegetarian refreshments is located, calculatesAnd S_{d_re}(i,j,t_l) correspondence position block of pixels phase Like spending, if the luminance matrix of two block of pixels is respectively M₁(i,j),M₂(i, j), then calculate similarity ρ using equation below：

$\mathrm{\ρ}=\frac{\underset{i}{\mathrm{\Σ}}\underset{j}{\mathrm{\Σ}}\left(M_1\left(i,j\right)-{\stackrel{\‾}{M}}_1\right)\left(M_2\left(i,j\right)-{\stackrel{\‾}{M}}_2\right)}{\underset{i}{\mathrm{\Σ}}\underset{j}{\mathrm{\Σ}}{\left(M_1\left(i,j\right)-{\stackrel{\‾}{M}}_1\right)}^2\underset{i}{\mathrm{\Σ}}\underset{j}{\mathrm{\Σ}}{\left(M_2\left(i,j\right)-{\stackrel{\‾}{M}}_2\right)}^2}$

WhereinWithFor the meansigma methodss of two pixel Block Brightness, calculateAnd S_{d_re}(i,j,t_l) all correspondence positions The similarity of block of pixels, if ρ is more than the similarity threshold for setting, then it is assumed that two block of pixels are identical, and by two-value In figure B (i, j), the pixel value of corresponding position is set to 1；Otherwise, the pixel value of binary map corresponding position is set to 0；Wherein 1 ≤i≤M/2,1≤j≤N/2.

4. the video frame in copy-move altering detecting method based on space-time relationship according to claim 1, its feature It is, the 7th step includes procedure below：

Step F1：If tampering detection algorithm detects m to there is the frame that copy-move is distorted, first according to the time of frame under Mark carries out sequential search to m to there is the frame that copy-move is distorted；When initial, scanned for the value of time index successively, will First pair of time index that there is the frame that copy-move is distorted is stored in two arrays respectively；

Step F2：There is the frame that copy-move is distorted in sequential search second pair：

If second pair has two frames that copy-move is distorted, its time index respectively with above two subscripts for being stored in array The absolute value of the difference of time is respectively less than or is equal to α₁T_threshold, then under the time that there is the frame that copy-move is distorted by second pair Mark in the array before being stored in respectively, wherein, α₁For adjusting thresholds coefficient；

If second pair of two time index that there is the frame that copy-move is distorted respectively with the previous lower timestamp for being stored in array Between difference absolute value be more than α₁T_threshold, then newly set up two arrays to deposit the time index of this pair of frames；

Next exist the time index of the frame pair that copy-move is distorted by with the frame deposited in all of array that sets up before Time index be compared, if be respectively less than to be equal to the time index absolute difference of element in all arrays before setting threshold Value, then be deposited in the closest array of time domain；If with the element time subscript absolute difference in all arrays before Given threshold is all higher than, then newly sets up two arrays to deposit the time index of this frame pair, until to all m pairs for detecting There is the frame that copy-move distorts to be grouped；The time index number included in different arrays is designated as n respectively_i, i=1,2, 3,...；

Step F3：To the packet subscript number n for obtaining_iThe threshold alpha obtained with step F2₁T_thresholdCompared as follows：

Work as n_i≥α₁T_thresholdWhen, then it is assumed that there is frame in copy-move and distort in the video；

Work as n_i＜ α₁T_thresholdWhen, then it is assumed that there is no frame in copy-move and distort in the video.