Video copy and paste blind detection method based on dense scale-invariant feature transform stream

Abstract

The invention discloses a video copy and paste blind detection method based on a dense scale-invariant feature transform (SIFT) stream. The video copy and paste blind detection method includes the following steps: step A, extracting key frames of video to be detected and non-key frames corresponding to each key frame; step B, confirming a copy area and a paste area of each key frame extracted in the step A so as to obtain a copy and paste detection result picture of each key frame; and step C, using a dense SIFT stream algorithm to obtain a copy and paste detection result of the video to be detected according to a copy and paste detection result of each key frame. Compared with the prior art, the video copy and paste blind detection method based on the dense SIFT stream is low in algorithm complexity, can accurately detect a copy and paste forgery area in the video, and has good robustness for rigid body target detection.

Description

technical field [0001] The invention relates to a blind detection method for copying and pasting videos based on dense SIFT streams, and belongs to the technical field of image processing. Background technique [0002] With the development of digital acquisition technology and digital video editing technology, the popularization of digital cameras and video cameras in households, the expansion of user groups such as iPhones and smart mobile terminals, the acquisition of media is becoming faster and more convenient, and accordingly individuals, units and the Internet There are a large number of video media documents accumulated in . These video documents are rich in content, widely used in various fields, and play a huge role in enriching the spiritual life of modern people. Using current video editing software, it is relatively easy to tamper with video content, for example, changing the background color through editing, highlighting the target, making the video more colorfu...

AI Technical Summary

Problems solved by technology

Usually, the frame-based copy detection method judges whether it is a copy forgery by comparing the similarity of the temporal-spatial correlation between video frames, but the pairwise comparison of the similarity requires a large amount of calculation and is not suitable for long video clips; the detection based on region copy The method is to realize the regional copy detection by estimating the similarity of the comprehensive features of pixels in a certain region (such as color, texture, noise, motion information or spatial position, etc.) The forged area has a good effect, it is difficult to find a small area, and the calculation is large, time-consuming, and the application range has certain limitations.

Images