Image copying and pasting detection method based on circular description operator CSIFT (Colored scale invariant feature transform)

Abstract

The invention relates to an image copying and pasting detection method based on circular description operator CSIFT (Colored scale invariant feature transform). The image copying and pasting detection method comprises the following steps: 1) inputting a colorful image, and calculating the color invariant of the colorful image, and taking the gradient direction of the color invariant as a direction characteristic; 2) detecting a scale space extremum line, and positioning key pints; 3) determining the main directions of the key points by utilizing a circular description operator to generate the 24-dimensional operators of all key points; 4) taking Euclidean distance between the operators of every two key points as measurement for judging key point similarity, pairing all key points in the image, determining two suspicious areas in the image, and finding all paired key points in the two suspicious areas; and 5) if the amount of the paired key points is greater than a set threshold value, judging that the image is tampered by copying and pasting, and otherwise, judging that the image is not tampered by copying and pasting. The method is favorable for accurately and efficiently detecting whether the same image is tampered by copying and pasting.

Description

technical field [0001] The invention relates to the technical field of image detection, in particular to an image copy-paste detection method based on a circle description operator CSIFT, which is suitable for copy-paste tampering detection of the same image. Background technique [0002] With the rapid development of image processing technology, digital image editing software is becoming more and more powerful, even non-professionals can easily tamper with image content. Copying and pasting of digital images is the most common and most covert means of tampering. Recently, many scholars have conducted research on copy-paste tampering detection technology. Wang Junwen et al proposed to use the Hu moment invariant eigenvector of the low-frequency block of the image pyramid to detect the image copy forgery area. Li Manman et al. proposed a blind detection algorithm based on wavelet transform and singular value decomposition to identify image copy-paste forgery. Luo Weiqi et ...

AI Technical Summary

Problems solved by technology

Although some research results have been obtained for the detection of image copy and paste tampering, there are still many practical problems to be solved. For example, the above algorithm can effectively defend against simple copy and paste, jpeg compression, Gaussian noise attacks, etc., but for geometric transformation attacks such as select zoom etc invalidation

Although the classic SIFT (Scale Invariant Feature Transform) algorithm can effectively deal with geometric transformation attacks, it is only suitable for detecting tampering of grayscale images, and the false matching rate is high when detecting color images, which greatly limits the scope of use of the algorithm

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