Digital video tampering detection method and system based on power grid frequency

Abstract

The invention discloses a digital video tampering detection method and system based on power grid frequency, and the method comprises the steps: deleting the visual content in a digital video to obtain the power grid frequency, enabling the power grid frequency to be embedded in a noise component of the digital video in an optical form, and carrying out the average processing in a column direction to obtain a line signal; filling the row signal of each frame in the idle time period to be zero, splicing all frames to construct a one-dimensional time sequence, and tracking a power grid frequency signal estimated value through S transformation; and matching the obtained power grid frequency signal estimation value with a reference frequency, and determining whether the digital video is tampered or not through frequency abrupt change. The invention aims to solve the problems of incomplete and distorted power grid frequency signals caused by time distortion in existing video power grid frequency estimation and the problem that high-precision extraction of the power grid frequency signals is restricted by complex background interference in a video recording process. Power grid frequency signals are accurately extracted, and high-precision detection and stable identification of video tampering behaviors are realized.

Description

Technical Field

[0001] This invention relates to the field of digital data detection technology, specifically to a method and system for detecting digital video tampering based on power grid frequency. Background Technology

[0002] With the rapid development and widespread application of digital video technology and artificial intelligence (AI), the authenticity and integrity of video content are receiving increasing attention. As a common form of digital forgery, digital video tampering (DVT) not only threatens information security but also poses serious challenges to forensic identification, media regulation, and other fields. Notably, as tampering techniques become increasingly sophisticated and easier to use, their threat is becoming more prominent. Furthermore, the rise of generative AI has further lowered the barrier to entry for producing high-quality forged videos, making it increasingly difficult to ensure the authenticity and integrity of video content. However, existing video tampering detection methods largely rely on visual features, which are often unable to withstand the influence of complex environments and diverse tampering methods, thus limiting detection performance. Therefore, developing effective DVT detection technologies has become particularly urgent.

[0003] In recent years, tamper detection technology based on Electric Network Frequency (ENF) signals has gradually become a research hotspot due to its unique trend consistency and temporal variability. Since most of the electricity in the power distribution network comes from turbines driving alternators, the turbine rotation speed determines the nominal frequency value of the power grid, with different standards in different countries. However, due to the constant changes in supply and demand in the power grid, the power grid signal fluctuates unpredictably over time, causing the power grid frequency to fluctuate around the nominal frequency. For example, if the nominal power grid frequency is 50Hz, this 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 tamper detection (DVT). Existing DVT detection methods based on power grid frequency are mainly based on reference frequency databases. First, the power grid frequency signal is directly extracted from the video, and then it is matched with a reference frequency database to determine the integrity of the video. Currently popular methods for extracting power grid frequencies include Short Time Fourier Transform (STFT), MUSIC, Rotation Invariant Technique (ESPRIT), Matrix Bundle (MP), Direct Connection (DCC), and Phase Method (PM). However, the existing power grid frequency extraction methods have the following technical problems: (1) Existing video power grid frequency extraction methods based on the rolling shutter mechanism ignore the non-uniform sampling effect caused by 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; this also means that existing video power grid frequency extraction methods cannot accurately characterize the time axis distortion caused by non-uniform sampling, resulting in spectral aliasing and energy distortion in the frequency domain of the line signal; (2) Due to complex background interference, the energy of the power grid frequency component is significantly weakened, resulting in severe distortion of the extracted power grid frequency signal, which in turn reduces the reliability of the matching result with the reference frequency. Existing video power grid frequency extraction methods have insufficient extraction accuracy under complex background interference conditions, resulting in reduced credibility of the matching result with the reference frequency. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a digital video tampering detection method and system based on power grid frequency, addressing the aforementioned problems in the prior art. This invention aims to solve the problems of incomplete and distorted power grid frequency signals caused by time distortion in existing video power grid frequency estimation, as well as the problem of high-precision extraction of power grid frequency signals restricted by complex background interference during video recording. It accurately extracts the power grid frequency signal and achieves high-precision detection and stable identification of video tampering behavior.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A digital video tampering detection method based on power grid frequency 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 position 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.

[0006] Optionally, 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.

[0007] Optionally, 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.

[0008] Optionally, the functional expression for performing the S-transform on the one-dimensional time series in step S105 is: ; ; in, This is a one-dimensional time series after 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.

[0009] Optionally, the peak tracking to obtain the grid frequency signal estimate in step S105 includes: S201, take the modulus of the one-dimensional time series after S-transformation 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 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, This is the estimated value of the power grid frequency signal corresponding to time index 𝑛. 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.

[0010] Optionally, 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. It is an integer.

[0011] Optionally, the calculation of similarity sequences The function expression is: ; in, This is the length of the time-frequency analysis window. For time index 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 The corresponding reference frequency, This represents the average value of the reference frequency within the time-frequency analysis window.

[0012] The present invention also provides a digital video tampering detection system based on power grid frequency, comprising a microprocessor and a memory interconnected thereto, wherein the microprocessor is programmed or configured to execute the digital video tampering detection method based on power grid frequency.

[0013] The present invention also provides a computer-readable storage medium storing a computer program or instructions that are programmed or configured to execute the power grid frequency-based digital video tampering detection method by a processor.

[0014] The present invention also provides a computer program product, including a computer program or instructions that are programmed or configured to execute the power grid frequency-based digital video tampering detection method via a processor.

[0015] Compared with existing technologies, the present invention mainly achieves the following beneficial effects: In order to effectively solve the shortcomings of video forensics methods based on power grid frequency in terms of power grid frequency signal modeling, non-uniform sampling effect processing, and complex background interference suppression, the method of the present invention includes a video signal model containing power grid frequency, which performs periodic zero-filling on the idle lines of each frame in the time dimension to reduce spectral aliasing caused by time axis distortion. Combined with the multi-resolution time-frequency analysis capability of S-transform, it effectively enhances the time-frequency expression capability of power grid frequency components, significantly improves the time-frequency clustering and energy expression of power grid frequency components, and realizes high-precision extraction of power grid frequency signals. It can solve the problems of incomplete and distorted power grid frequency signals caused by time distortion in existing video power grid frequency estimation and the problem of complex background interference restricting the high-precision extraction of power grid frequency signals during video recording. It can improve the estimation accuracy and robustness of power grid frequency signals, accurately extract power grid frequency signals, and realize high-precision detection and stable identification of video tampering behavior. This invention can maintain high accuracy and stability in extracting power grid frequencies even under complex background interference conditions. By matching with a reference frequency, it can effectively identify the authenticity and tampering of digital videos, thereby improving the reliability of identification and media evidence collection. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the basic process of the method in an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of the system structure of the signal acquisition and processing system in an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram of the camera video acquisition process based on the rolling shutter mechanism in an embodiment of the present invention.

[0019] Figure 4 This is a comparison between the extracted power grid frequency signal estimate (PZST) and the reference frequency in this embodiment of the invention.

[0020] Figure 5 This is a comparison between the power grid frequency signal estimate (PZST) extracted in this embodiment of the invention and the reference frequency, where (a) is a deletion tampering and (b) is an insertion tampering. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be further described in detail below with reference to the accompanying drawings in the embodiments of the present invention.

[0022] like Figure 1 As shown, the digital video tampering detection method based on power grid frequency in this embodiment 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 position 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.

[0023] like Figure 2 As shown, the signal acquisition and processing system in this embodiment consists of lighting equipment, a grid situational awareness device (GSAD), and a recording device (laptop or camera). The recording device records digital video and simultaneously captures the grid frequency signal characteristics carried by changes in the light intensity of the lighting equipment, thus acquiring the grid frequency signal at the video end. Simultaneously, the GSAD records the grid voltage and extracts the reference frequency. It is then stored in a database, enabling synchronous storage and comparison with the power grid frequency signal at the video end.

[0024] In digital video acquired using a rolling shutter mechanism, the power grid frequency signal is typically embedded in the visual content of the video as optical interference, which can be expressed as: ; in, For digital video signals, where For row index, For column indexes, For frame indexing; For the visual content of digital video; This represents the noise component of the digital video.

[0025] When power grid frequency signals are embedded in video, pixel positions corresponding to different visual content may exhibit different amplitude responses. To address this effect, we model it as an additive noise term. Therefore, noise components It can be represented as: ; in, It contains the power grid frequency signal to be estimated.

[0026] It is a periodically changing signal, which can be represented as: ; in, It's the amplitude. It is the nominal power grid frequency. Indicates frame index The changing phase.

[0027] To achieve accurate estimation of the power grid frequency signal, it is first necessary to remove visual content from the video, followed by noise component... Averaging is performed along the column direction to obtain the row signal. Since video capture typically uses a rolling shutter mechanism for line-by-line sampling, there are certain idle time periods within each frame. To ensure temporal consistency across frames and avoid information loss, this invention performs line-by-line sampling on each frame. L +1 line to the M The idle time period of each row is filled with zeros. In step S103, the first... 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 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: ; 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 value of the sampling point count of the read digital video will include some lines that do not have idle time periods. Since these lines do not have idle time periods, there is no need to fill the idle time periods with zeros, and this is consistent with the preset line threshold. The value is taken as each frame period when using the rolling shutter mechanism for line-by-line sampling. Internal readout time The number of sampling points of the read digital video is the same, except that there are some extra lines of idle time periods for reading and judgment.

[0028] To improve the robustness and accuracy of power grid frequency signal estimation in low signal-to-noise ratio environments, this embodiment employs the S-transform for frequency estimation. The S-transform is a time-frequency analysis method proposed by Stockwell et al. in 1996. It combines the advantages of the Short-Time Fourier Transform (STFT) and the CWT, providing multi-resolution time-frequency representations while preserving phase information. The functional expression for performing the S-transform on the one-dimensional time series in step S105 of this embodiment 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.

[0029] In step S105 of this embodiment, peak tracking is performed to obtain the estimated value of the power grid frequency signal. f est include: S201, taking the modulus of the one-dimensional time series after S-transformation to obtain the time-frequency amplitude spectrum, can be expressed as: ; in, The time-frequency amplitude spectrum, To Take the modulo value. The time-spectral function of the S-transform; 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 In the index set Find the frequency index with the largest amplitude in the time-frequency amplitude spectrum. , can be represented as: ; S204, index the frequency with the largest amplitude. The following formula maps to the estimated value of the power grid frequency signal. fest : ; in, The estimated value of the power grid frequency signal corresponding to time index 𝑛 f est , 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 The readout time within the range. This includes the line sampling frequency when using a rolling shutter mechanism for line-by-line sampling. for: ; in, The sampling interval between two adjacent rows. For frame period, To read out the time period, It is the total number of lines in a frame. This is the preset row threshold. Because the power grid frequency signal is embedded into the video recording captured by the camera through changes in light intensity, its fluctuation frequency is the nominal power grid frequency. Twice that. The instantaneous value of the grid frequency signal fluctuates around the nominal value, but its range of variation is typically narrow (e.g., 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 grid frequency trajectory is only... The values ​​at these locations are non-zero, and their periods are respectively... and Therefore, 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. It is an integer, and its value can be searched as needed.

[0030] In this embodiment, the calculation of similarity sequences The function expression is: ; in, This is the length of the time-frequency analysis window. For time index 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 The corresponding reference frequency, This represents the average value of the reference frequency within the time-frequency analysis window.

[0031] To verify the effectiveness of the digital video tampering detection method based on power grid frequency in this embodiment, Adobe Premiere was used to perform two types of editing operations on the original video: frame deletion and frame insertion. Figure 4 This example compares the power grid frequency extracted from the original video with the reference frequency. Figure 5 This embodiment compares the power grid frequency extracted from the tampered video with the reference frequency, where (a) represents deletion tampering and (b) represents insertion tampering. Figure 4 and Figure 5 In this embodiment, PZST represents the estimated power grid frequency extracted by the digital video tampering detection method based on power grid frequency, and CC represents the similarity between the two curve segments. From... Figure 4 and Figure 5 It can be seen that, under untampered conditions, the power grid frequency extracted from the video and the reference frequency acquired by GSAD maintain good overlap throughout the entire time period, with peak and valley positions basically consistent and no obvious discontinuities, and the similarity between the two is as high as 0.9936. Conversely, in the tampered video, the extracted power grid frequency estimate relative to the reference frequency shows a significant abrupt change around 5 minutes (i.e., the difference between the power grid frequency estimate and the reference frequency exceeds the preset threshold), accompanied by peak and valley misalignment and short-term spikes, resulting in a significant decrease in similarity. Therefore, it can be determined that the video has been tampered with. At the same time, the type of tampering can be detected based on the abrupt change and its duration. Frame deletion usually manifests as spikes and phase shifts caused by local time compression, while frame insertion often manifests as spikes and phase shifts caused by time dilation. It can be seen that the digital video tampering detection method based on power grid frequency in this embodiment first addresses the non-uniform sampling effect caused by readout time and idle period under the rolling shutter mechanism by periodically zero-filling the idle lines of each frame in the temporal dimension to restore the time axis integrity of the line signal. Subsequently, the zero-filled row signal is processed using the multi-resolution time-frequency analysis capability of the S-transform to enhance the time-frequency clustering and energy expression of the power grid frequency components, thereby improving the estimation accuracy and noise resistance of the power grid frequency signal. Based on this, this embodiment constructs a digital video power grid frequency extraction and tampering detection system using a power grid frequency-based digital video tampering detection method. By stably matching the extracted power grid frequency signal with a reference frequency database, high-precision detection and reliable identification of video tampering behavior are achieved. This embodiment's power grid frequency-based digital video tampering detection method not only effectively solves the signal distortion and spectral aliasing problems caused by non-uniform sampling in existing technologies, but also significantly improves the power grid frequency extraction accuracy under complex background interference conditions, thereby enhancing the robustness and reliability of digital video tampering detection.

[0032] This embodiment also provides a digital video tampering detection system based on power grid frequency, including a microprocessor and a memory interconnected, wherein the microprocessor is programmed or configured to execute the digital video tampering detection method based on power grid frequency.

[0033] This embodiment also provides a computer-readable storage medium storing a computer program or instructions that are programmed or configured to execute the power grid frequency-based digital video tampering detection method via a processor.

[0034] This embodiment also provides a computer program product, including a computer program or instructions that are programmed or configured to execute the power grid frequency-based digital video tampering detection method via a processor.

[0035] Those skilled in the art will understand that the technical solutions provided by this invention may take the form of a method, system, or computer program product. Therefore, this invention may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this invention may take the form of a computer program product embodied on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, produce an implementation of the flowchart... Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0036] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

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 position 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 if there is a frequency change. If a frequency change is found, the digital video is determined to have been tampered with.

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, 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 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, This is the estimated value of the power grid frequency signal corresponding to time index 𝑛. 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.

6. The digital video tampering detection method based on power grid frequency according to claim 5, 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. It is an integer.

7. 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 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 The corresponding reference frequency, This represents the average value of the reference frequency within the time-frequency analysis window.

8. 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 7.

9. 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 7.

10. 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 7.

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