A digital video tampering detection method and system based on power grid frequency

Abstract

The application discloses a kind of digital video tampering detection method and system based on power grid frequency, the method of the application includes deleting visual content in digital video to obtain the noise component of power grid frequency to be embedded in digital video in optical form, average processing is carried out in column direction to obtain line signal;The line signal of each frame idle time period is filled to zero, and all frames are spliced to construct one-dimensional time sequence, and the power grid frequency signal estimate value is tracked by S transform;The obtained power grid frequency signal estimate value is matched with reference frequency, and whether digital video is tampered with is determined by frequency mutation.The application aims to solve the problem of incomplete and distorted power grid frequency signal caused by time distortion in existing video power grid frequency estimation, and the problem of high-precision extraction of power grid frequency signal restricted by complex background interference in video recording process, accurately extract the power grid frequency signal, realize high-precision detection and stable discrimination on video tampering behavior.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital data detection, and particularly relates to a digital video tampering detection method and system based on power grid frequency. BACKGROUND

[0002] With the rapid development and wide application of digital video technology and artificial intelligence (AI), the authenticity and integrity of video content are attracting more and more attention. As a common means of digital forgery, digital video tampering (DVT) not only threatens information security, but also poses a serious challenge to the fields of judicial expertise and media supervision. It is worth noting that with the continuous concealment and ease of tampering technology, its threat is increasingly prominent, and the rise of generative artificial intelligence (Generative AI) further lowers the threshold for producing high-quality fake videos, making it increasingly difficult to protect the authenticity and integrity of video content. However, existing video tampering detection methods often rely on visual features, which are often difficult to resist the influence of complex environments and diverse tampering methods, thus limiting the detection performance. Therefore, it is particularly urgent to develop effective DVT detection technology.

[0003] In recent years, tamper detection technology based on electric network frequency (ENF) signal has gradually become a research hotspot due to its unique trend consistency and time difference. Because most of the power in the distribution network of the power grid comes from the turbine driving the alternator, the rotational speed of the turbine determines the nominal frequency value of the power grid frequency, and different countries have different standards. However, due to the continuous change of supply and demand in the power grid, the power grid signal fluctuates unpredictably over time, causing the power grid frequency to fluctuate above and below the nominal power grid frequency. For example, the nominal power grid frequency is 50Hz, and the fluctuation range is generally between 49.9Hz and 50.1Hz, and this fluctuation is completely random and unpredictable. The power grid frequency signal is inevitably embedded in the video during video recording, providing strong support for DVT detection. The existing DVT detection method based on power grid frequency is mainly a detection method based on a reference frequency database. First, the power grid frequency signal is directly extracted from the video, and then it is matched with the reference frequency database to determine the integrity of the video. The popular power grid frequency extraction methods include short-time Fourier transform (STFT), MUSIC, rotation invariant technology (ESPRIT), matrix pencil (MP), direct connection method (DCC) and phase method (PM). However, the existing power grid frequency extraction methods have the following technical problems: (1) The existing video power grid frequency extraction method based on the rolling shutter mechanism ignores the non-uniform sampling effect caused by the readout time and idle period in signal modeling, and cannot accurately reflect the time axis structure. Therefore, the extracted line signal will have spectral aliasing and energy distortion in the frequency domain, resulting in insufficient accuracy of power grid frequency estimation; the existing video power grid frequency extraction method cannot accurately depict the time axis distortion caused by non-uniform sampling, resulting in spectral aliasing and energy distortion of the line signal in the frequency domain; (2) Due to complex background interference, the energy of the power grid frequency component is significantly weakened, causing the extracted power grid frequency signal to be severely distorted, thereby reducing the reliability of the matching result with the reference frequency. The existing video power grid frequency extraction method has insufficient extraction accuracy under complex background interference, resulting in reduced reliability of the matching result with the reference frequency. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a digital video tamper detection method and system based on power grid frequency, which can accurately extract the power grid frequency signal and realize high-precision detection and stable identification of video tampering behavior.

[0005] To solve the above technical problems, the technical scheme adopted by the present application is:

[0006] A digital video tampering detection method based on grid frequency, comprising the following steps:

[0007] S101, for a digital video sampled by a rolling shutter mechanism, deleting visual content in the digital video to obtain a noise component in which a grid frequency is optically embedded in the digital video;

[0008] S102, averaging the noise component of each frame in the column direction to obtain a row signal;

[0009] S103, filling the idle time period from the first row to the row of each frame with zero, wherein is a preset row threshold, is the number of rows of each frame;

[0010] S104, splicing all the frames filled with zero to construct a one-dimensional time sequence;

[0011] S105, performing S transform on the one-dimensional time sequence, and performing peak tracking to obtain a grid frequency signal estimate;

[0012] S106, performing sliding point-by-point matching between the grid frequency signal estimate and a reference frequency recorded synchronously with the digital video to calculate a similarity sequence , searching for the position corresponding to the maximum similarity sequence ;

[0013] S107, taking the position as a starting point, performing point-by-point comparison between the reference frequency r recorded synchronously with the digital video and the grid frequency signal estimate to determine whether there is a frequency mutation, and if there is a frequency mutation, determining that the digital video is tampered.

[0014] Optionally, the function expression for filling the idle time period from the first row to the row of each frame with zero in step S103 is:

[0015] ;

[0016] wherein, and are the row signal after zero filling and the original row signal of the first frame respectively, is a time index, is a readout time, is a frame period.

[0017] ​​​Optionally, the preset row threshold is the readout time period for each frame cycle when sampling row by row with a rolling shutter mechanism is the readout time period is the number of sampling points of the readout digital video is the readout time period is the idle time period is the idle time period when sampling row by row with a rolling shutter mechanism no action of reading sampling points is performed within the idle time period.

[0018] Optionally, the function expression of the one-dimensional time sequence in step S105 is:

[0019] ;

[0020] ;

[0021] wherein, is the one-dimensional time sequence after S transform, is the time index, is the frequency index, is the length of the time-frequency analysis window, is the input one-dimensional time sequence before transform, is the window function, is the m-th frequency point, is the imaginary unit.

[0022] Optionally, the peak tracking in step S105 to obtain the power grid frequency signal estimation value comprises:

[0023] S201, taking the modulus value of the one-dimensional time sequence after S transform to obtain a time-frequency amplitude spectrum;

[0024] S202, determining the main peak of the one-dimensional time sequence , and selecting a frequency search interval centering on the main peak and in combination with the frequency interval ;

[0025] S203, for each time index , finding the frequency index with the maximum amplitude in the time-frequency amplitude spectrum in the index set ;

[0026] S204, mapping the frequency index with the maximum amplitude to the power grid frequency signal estimation value according to the following formula: ​​

[0027] ;

[0028] wherein, is the grid frequency signal estimate value corresponding to the time index n, is the time-frequency analysis window length, is the row sampling frequency with a rolling shutter mechanism, , is the readout time within each frame period when sampling row by row with a rolling shutter mechanism, is the preset row threshold.

[0029] Optionally, the function expression of the main peak of the one-dimensional time sequence determined in step S202 is:

[0030] ;

[0031] wherein, is the nominal grid frequency, is the row sampling frequency with a rolling shutter mechanism, is an integer.

[0032] Optionally, the function expression of the similarity sequence is:

[0033] ;

[0034] wherein, is the time-frequency analysis window length, is the grid frequency signal estimate value corresponding to the time index n, is the average value of the grid frequency signal estimate value within the time-frequency analysis window, is the reference frequency corresponding to the time index n, is the average value of the reference frequency within the time-frequency analysis window. The present application also provides a grid frequency-based digital video tampering detection system, comprising a microprocessor and a memory connected to each other, the microprocessor being programmed or configured to execute the grid frequency-based digital video tampering detection method.

[0035] The present application also provides a computer readable storage medium having a computer program or instructions stored therein, the computer program or instructions being programmed or configured to execute the grid frequency-based digital video tampering detection method by a processor.

[0036] The present application also provides a computer readable storage medium having a computer program or instructions stored therein, the computer program or instructions being programmed or configured to execute the grid frequency-based digital video tampering detection method by a processor.

[0037] ​​The application also provides a computer program product comprising a computer program or instructions programmed or configured to execute the digital video tampering detection method based on power grid frequency by a processor.

[0038] Compared with the prior art, the application mainly has the following beneficial effects: in order to effectively solve the problems of the video forensics method based on power grid frequency in power grid frequency signal modeling, non-uniform sampling effect processing and complex background interference suppression, the method comprises periodic zero padding of idle rows of each frame in the time dimension based on a video signal model containing power grid frequency, so as to weaken spectral aliasing caused by time axis distortion, effectively enhance the time-frequency expression ability of the power grid frequency component by combining the multi-resolution time-frequency analysis ability of S transform, significantly improve the time-frequency aggregation and energy expression of the power grid frequency component, realize high-precision extraction of the power grid frequency signal, solve the problems of incomplete and distorted power grid frequency signal caused by time distortion in the existing video power grid frequency estimation and the problem of complex background interference in the video recording process restricting high-precision extraction of the power grid frequency signal, improve the estimation precision and robustness of the power grid frequency signal, accurately extract the power grid frequency signal, and realize high-precision detection and stable identification of video tampering behavior. The application can still maintain high power grid frequency extraction precision and stability under complex background interference conditions, effectively identify the authenticity and tampering behavior of digital video by matching with a reference frequency, and improve the reliability of identification and media forensics. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 It is a basic flowchart of the method of the embodiment of the application.

[0040] Figure 2 It is a system structure diagram of the signal acquisition and processing system in the embodiment of the application.

[0041] Figure 3 It is a camera video acquisition process diagram based on the rolling shutter mechanism in the embodiment of the application.

[0042] Figure 4 It is a comparison of the extracted power grid frequency signal estimation value (PZST) and the reference frequency in the embodiment of the application.

[0043] Figure 5 It is a comparison of the extracted power grid frequency signal estimation value (PZST) and the reference frequency in the embodiment of the application, wherein (a) is deletion tampering and (b) is insertion tampering. DETAILED DESCRIPTION

[0044] In order to enable personnel in the technical field to better understand the technical solutions of the application, the technical solutions of the application will be further described in detail below with reference to the drawings in the embodiments of the application.

[0045] As Figure 1 shown, the digital video tampering detection method based on grid frequency in the embodiment includes the following steps:

[0046] S101, for the digital video sampled by the rolling shutter mechanism, deleting the visual content in the digital video to obtain the noise component in which the grid frequency is optically embedded in the digital video;

[0047] S102, averaging the noise component of each frame in the column direction to obtain the line signal;

[0048] S103, filling the idle time period from the first row to the row of each frame with zero, wherein is a preset row threshold, is the number of rows of each frame;

[0049] S104, splicing all the frames filled with zero to construct a one-dimensional time sequence;

[0050] S105, performing S transform on the one-dimensional time sequence, and performing peak tracking to obtain the grid frequency signal estimation value;

[0051] S106, performing sliding point-by-point matching on the grid frequency signal estimation value and the reference frequency recorded synchronously with the digital video to calculate the similarity sequence , searching for the position corresponding to the maximum similarity sequence ;

[0052] S107, starting from the position , performing point-by-point comparison between the reference frequency r recorded synchronously with the digital video and the grid frequency signal estimation value to determine whether there is a frequency mutation, and if there is a frequency mutation, it is determined that the digital video is tampered.

[0053] As Figure 2 shown, the signal acquisition and processing system in the embodiment is composed of a lighting device, a grid situational awareness device (GSAD) and a recording device (a notebook computer or a camera). The recording device records the digital video, and synchronously captures the grid frequency signal features carried by the illumination intensity change of the lighting device, so as to realize the acquisition of the video-end grid frequency signal. At the same time, the grid situational awareness device records the grid voltage and extracts the reference frequency and stores it into a database, so that the synchronous storage and comparison with the video-end grid frequency signal can be realized.

[0054] ​Based on the digital video collected by the rolling shutter mechanism, the power grid frequency signal is usually embedded in the visual content of the video in the form of optical interference, and its expression can be expressed as:

[0055]

[0056] wherein, is the signal of the digital video, wherein is the row index, is the column index, is the frame index; is the visual content of the digital video; is the noise component of the digital video.

[0057] When the power grid frequency signal is embedded in the video, different visual content corresponding to the pixel position may exhibit different amplitude responses. For this effect, we model it as an additive noise item , so the noise component can be expressed as:

[0058]

[0059] wherein, contains the power grid frequency signal to be estimated.

[0060] is a periodically changing signal, which can be expressed as:

[0061]

[0062] wherein, is the amplitude, is the nominal power grid frequency, represents the phase varying with the frame index .

[0063] To achieve accurate estimation of the power grid frequency signal, the visual content needs to be removed from the video first, and then the noise component is averaged in the column direction to obtain the row signal . Since the video is usually collected by the rolling shutter mechanism for line-by-line sampling, there is a certain idle time period in each frame signal. In order to ensure the consistency of each frame signal in time and avoid information loss, the present application fills the idle time period from the L +1th row to the M th row of each frame with zero. The function expression for filling the idle time period from the th row to the th row of each frame with zero in step S103 is:

[0064] ;​​​​

[0065] in, and The first The line signal after frame zero-padding and the original line signal, For time indexing, To read the time, The frame period is defined. The signals from all frames are concatenated to construct a one-dimensional time series. According to multi-rate signal processing theory, one-dimensional time series... Spectrum This can be expressed as a weighted sum of shifts in the spectrum of the line signal:

[0066] ;

[0067] in, For frame rate, For frame period, This refers to the line sampling frequency used when sampling line by line using a rolling shutter mechanism. The weights are constants. For example... Figure 3 As shown, the preset row threshold in this embodiment To use the rolling shutter mechanism for line-by-line sampling, each frame period Internal readout time The number of sampling points and frame period of the digital video read. To read out the time period Free time The sum of the two represents the idle time period when using a rolling shutter mechanism for line-by-line sampling. The action of reading sampling points is not performed during the readout time. During this period, pixels moved from row 1 to row 2. The rows are exposed sequentially. During the idle period... During this period, the sensor does not generate valid observation samples until the start of the next frame. Therefore, the time axis exhibits a non-uniform sampling structure with alternating "dense sequential sampling - idle gaps," and satisfies... For power grid frequency extraction, each line of the video frame is considered a sampling point. Alternatively, a preset line threshold can be used. The value is greater than the frame period when using the rolling shutter mechanism for line-by-line sampling. Internal readout time The value of the number of sampling points in the read digital video will reduce the number of rows filled with zeros during idle periods, which will affect the effectiveness of the method in this embodiment; a preset row threshold can also be used. The value is less than the frame period when using the rolling shutter mechanism for line-by-line sampling. Internal readout time The read-out number of sampling points of the digital video, at this time, some rows without the idle time period are included, and the operation of filling the idle time period with zero is not needed for these rows, and the preset row threshold The value of each frame period when the rolling shutter mechanism is used for row sampling The internal read-out time The read-out number of sampling points of the digital video is the same, but there are some redundant read-out and judgment operations of the idle time period of the extra rows.

[0068] In order to improve the estimation robustness and accuracy of the power grid frequency signal in a low signal-to-noise ratio environment, S transform is used for frequency estimation in the embodiment. S transform is a time-frequency analysis method proposed by Stockwell et al. in 1996. It combines the advantages of short-time Fourier transform (STFT) and wavelet transform (CWT), and can provide multi-resolution time-frequency representation while maintaining phase information. The function expression for S transform of a one-dimensional time series in step S105 of the embodiment is as follows:

[0069] ;

[0070] ;

[0071] wherein, is the time-frequency spectrum function of S transform, and is the time index, is the frequency index, is the time-frequency analysis window length, is the input one-dimensional time series before transformation, is the window function, is the th frequency point, is the imaginary unit.

[0072] The peak value tracking in step S105 of the embodiment obtains the power grid frequency signal estimation value f est comprises:

[0073] S201, the modulus value of the one-dimensional time series after S transform is obtained to obtain the time-frequency amplitude spectrum, which can be expressed as:

[0074] ;

[0075] wherein, is the time-frequency amplitude spectrum, is the modulus value of , and is the time-frequency spectrum function of S transform;

[0076] S202, determining the main peak of the one-dimensional time series , centered at the main peak, a frequency interval is selected , and a corresponding index set is determined ;

[0077] S203, for each time index , find the frequency index with the largest amplitude in the time-frequency amplitude spectrum in the index set , , which can be expressed as: ;

[0078] S204, map the frequency index with the largest amplitude to the power grid frequency signal estimate value according to the following formula f est :

[0079] ;

[0080] wherein is the power grid frequency signal estimate value corresponding to the time index f est , is the time-frequency analysis window length, is the row sampling frequency with the rolling shutter mechanism, is the readout time within each frame period when sampling row by row with the rolling shutter mechanism. The row sampling frequency with the rolling shutter mechanism is:

[0081] ;

[0082] wherein is the interval between adjacent two rows of sampling, is the frame period, is the readout time period, is the total number of rows in a frame, is a preset row threshold value. Since the power grid frequency signal is embedded into the video recording captured by the camera through light intensity changes, its fluctuation frequency is twice the nominal power grid frequency . The instantaneous value of the power grid frequency signal fluctuates around the nominal value, but its change range is usually narrow (for example, 49.90-50.10 Hz in China and 59.90-60.10 Hz in the United States). Therefore, it is assumed that the frequency domain representation of the pure power grid frequency trajectory is only non-zero at , and its period is and ​​Therefore, the main peak of the one-dimensional time sequence is determined in step S202 The function expression of the main peak is:

[0083] ;

[0084] wherein, is the nominal grid frequency, is the row sampling frequency by using the rolling shutter mechanism to sample row by row, is an integer, and the value thereof can be searched according to requirements.

[0085] In the embodiment, the function expression of the similarity sequence is:

[0086] ;

[0087] wherein, is the time-frequency analysis window length, is the time index corresponding to the grid frequency signal estimation value, is the average value of the grid frequency signal estimation value in the time-frequency analysis window, is the time index corresponding to the reference frequency, is the average value of the reference frequency in the time-frequency analysis window.

[0088] In order to verify the effectiveness of the digital video tampering detection method based on the grid frequency in the embodiment, Adobe Premiere is used to perform two types of editing operations, frame deletion and frame insertion, on the original video. Figure 4 is the comparison between the grid frequency and the reference frequency extracted from the original video in the embodiment, Figure 5 is the comparison between the grid frequency and the reference frequency extracted from the tampered video in the embodiment, wherein (a) is deletion tampering, and (b) is insertion tampering. Figure 4 and Figure 5 In the embodiment, PZST is the grid frequency estimation value extracted by the digital video tampering detection method based on the grid frequency, and CC is the similarity of the two curves. From Figure 4 and Figure 5As can be seen, in the non-tampered condition, the power grid frequency extracted from the video coincides well with the reference frequency collected by the GSAD in the whole period, the peak and valley positions are basically consistent and there is no obvious discontinuity, and the similarity is as high as 0.9936. In contrast, in the tampered video, the estimated value of the power grid frequency extracted from the video has an obvious mutation (i.e., the difference between the estimated value of the power grid frequency and the reference frequency exceeds the preset threshold) near 5 min, and is accompanied by peak and valley misalignment and short-time spikes, resulting in a significant decrease in similarity. Therefore, it can be determined that the video is tampered. At the same time, the type of tampering can be detected according to the mutation and the duration, and frame deletion usually exhibits spikes and phase advance caused by local time compression, while frame insertion usually exhibits spikes and phase lag caused by time expansion. As can be seen, the digital video tampering detection method based on the power grid frequency of the embodiment first addresses the non-uniform sampling effect caused by the readout time and the idle period under the rolling shutter mechanism, periodically fills the idle rows of each frame with zeros in the time dimension to restore the time axis integrity of the row signal. Subsequently, the row signal after zero filling is processed using the multi-resolution time-frequency analysis capability of the S transform to enhance the time-frequency concentration and energy expression of the power grid frequency component, thereby improving the estimation accuracy and noise immunity of the power grid frequency signal. On this basis, the digital video tampering detection method based on the power grid frequency of the embodiment constructs a digital video power grid frequency extraction and tampering detection system, which realizes high-precision detection and reliable identification of video tampering behavior by stably matching the extracted power grid frequency signal with the reference frequency database. The digital video tampering detection method based on the power grid frequency of the embodiment not only effectively solves the signal distortion and spectral aliasing problem caused by non-uniform sampling in the prior art, but also significantly improves the power grid frequency extraction accuracy under complex background interference conditions, thereby improving the robustness and reliability of digital video tampering detection.

[0089] The embodiment also provides a digital video tampering detection system based on a power grid frequency, which comprises a microprocessor and a memory connected to each other, and the microprocessor is programmed or configured to execute the digital video tampering detection method based on the power grid frequency.

[0090] The embodiment also provides a computer-readable storage medium, which stores a computer program or instructions programmed or configured to execute the digital video tampering detection method based on the power grid frequency by a processor.

[0091] The embodiment also provides a computer program product, which comprises a computer program or instructions programmed or configured to execute the digital video tampering detection method based on the power grid frequency by a processor.

[0092] Those skilled in the art will appreciate that the technology provided herein is not limited to any particular form of implementation. The technology provided herein can be implemented in hardware, software, or a combination thereof. Those skilled in the art will appreciate that the technology provided herein can be implemented in a number of different embodiments, including method embodiments, system embodiments, and computer program product embodiments. The technology provided herein can be implemented in any combination of hardware, software, or a combination thereof. The technology provided herein can be implemented in a number of different ways, including as a computer program product stored on a computer readable storage medium, as a system on chips (SOCs), as an application specific integrated circuit (ASIC), or as a cloud service. The computer program product can be implemented using two or more computer program Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks

[0093] The above description is only preferred embodiments of the present application, the protection scope of the present application is not limited to the above-mentioned embodiments, any technical scheme falling within the idea of the present application shall be considered as falling within the protection scope of the present application. It should be noted that, for ordinary skilled in the art, some improvements and refinements without departing from the principle of the present application shall be considered as falling within the protection scope of the present application.

Claims

1. A digital video tampering detection method based on power grid frequency, characterized in that, Includes the following steps: S101, for digital video that uses a rolling shutter mechanism for line-by-line sampling, removes visual content from the digital video to obtain the noise component of the power grid frequency embedded in the digital video in an optical form; S102, the noise components of each frame are averaged in the column direction to obtain the row signal; S103, the first frame of each frame Arrive at the The idle time period of the row is filled with zeros, where The preset row threshold, The number of lines in each frame; S104, stitch together all zero-padded frames to construct a one-dimensional time series; S105, perform S-transform on the one-dimensional time series and perform peak tracking to obtain the estimated value of the power grid frequency signal; S106, compare the estimated power grid frequency signal with the reference frequency recorded synchronously with the digital video. Perform sliding point-by-point matching to calculate similarity sequences Search for the sequence with the highest similarity. Corresponding position ; S107, in terms of location Starting from this point, a reference frequency will be recorded synchronously with the digital video. r The digital video is compared point by point with the estimated power grid frequency signal to determine whether there is a frequency change. If a frequency change is found, the digital video is determined to have been tampered with. Step S105, which involves peak tracking to obtain the grid frequency signal estimate, includes: S201, take the modulus of the time-frequency spectrum function of the S-transform to obtain the time-frequency amplitude spectrum; S202, Determine the main peak of the one-dimensional time series. With the main peak Centered on, combined with frequency intervals Select frequency search range And determine the corresponding set of indices. ; S203, for each time index n In the index set Find the frequency index with the largest amplitude in the time-frequency amplitude spectrum. ; S204, index the frequency with the largest amplitude. The following formula maps to the estimated value of the power grid frequency signal: ； in, For time index n The corresponding power grid frequency signal estimate, This is the length of the time-frequency analysis window. This refers to the line sampling frequency used when sampling line by line using a rolling shutter mechanism. , To use the rolling shutter mechanism for line-by-line sampling, each frame period Read time within, This is the preset row threshold.

2. The digital video tampering detection method based on power grid frequency according to claim 1, characterized in that, In step S103, the first frame of each frame is... Arrive at the idle time of line The function expression filled with zeros is: ； in, and The first The line signal after frame zero-padding and the original line signal, For time indexing, To read the time, The frame period.

3. The digital video tampering detection method based on power grid frequency according to claim 1, characterized in that, The preset row threshold To use the rolling shutter mechanism for line-by-line sampling, each frame period Internal readout time The number of sampling points of the read digital video, the frame period To read out the time period Free time The sum of the two represents the idle time period when using a rolling shutter mechanism for line-by-line sampling. The action of reading sampling points is not performed internally.

4. The digital video tampering detection method based on power grid frequency according to claim 1, characterized in that, The functional expression for performing the S-transform on the one-dimensional time series in step S105 is: ； ； in, The time-frequency spectrum function of the S-transform. and For time indexing, For frequency index, This is the length of the time-frequency analysis window. The input is a one-dimensional time series before transformation. For window functions, For the first Each frequency point, It is the imaginary unit.

5. The digital video tampering detection method based on power grid frequency according to claim 4, characterized in that, In step S202, the main peak of the one-dimensional time series is determined. The function expression is: ； in, The nominal grid frequency, This refers to the line sampling frequency used when sampling line by line using a rolling shutter mechanism. and It is an integer.

6. The digital video tampering detection method based on power grid frequency according to claim 1, characterized in that, The similarity sequence is calculated The function expression is: ； in, This is the length of the time-frequency analysis window. For time index i The corresponding power grid frequency signal estimate, This represents the average value of the estimated power grid frequency signal within the time-frequency analysis window. For time index i The corresponding reference frequency, This represents the average value of the reference frequency within the time-frequency analysis window.

7. A digital video tampering detection system based on power grid frequency, comprising a microprocessor and a memory interconnected, characterized in that, The microprocessor is programmed or configured to execute the digital video tampering detection method based on power grid frequency as described in any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program or instructions, characterized in that, The computer program or instructions are programmed or configured to execute, via a processor, the digital video tampering detection method based on power grid frequency as described in any one of claims 1 to 6.

9. A computer program product, comprising a computer program or instructions, characterized in that, The computer program or instructions are programmed or configured to execute, via a processor, the digital video tampering detection method based on power grid frequency as described in any one of claims 1 to 6.

Images