Main Article Content
. Surveillance cameras are generally used in real-time scenarios to provide assurance and security. These
videos often serve as crucial evidence in court proceedings. Currently, technology is growing rapidly, resulting in
the availability of various editing tools, which are essential for checking the integrity and trustworthiness of video
content. Forgery detection is most commonly accomplished through pixel-correlation methods that take a long time
to calculate since each pixel of a video frame is compared to identify a forgery. So, the statistical value-based
histogram approach effectively detected inter-frame forgeries such as frame insertion, deletion, and duplication. This
paper proposes a method to detect forged videos using Histograms of Gradients (HOG) with Discrete Wavelet
Transform (DWT). The experimental outcome suggests that the proposed method is more accurate than the existing
method and gives a 0.98 accuracy score with a faster execution time.
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