Sobel edge detection and image block brightness feature-based blind image tampering forensic method

Abstract

The invention discloses a Sobel edge detection and image block brightness feature-based blind image tampering forensic method. The method is characterized by comprising the following steps of: converting a to-be-detected suspicious image into a grayscale image; carrying out convolution processing on the grayscale image I (i, j); obtaining a gradient image G (i, j) of the image; carrying out threshold value segmentation on the G (i, j) to obtain the gradient image G (i, j); carrying out binary processing on the gradient image G (i, j) to obtain a binary image W (i, j); carrying 1 pixelation on the binary image; and judging the similarity of two sub-image sets. According to the method, blocking processing is carried out on image sets; through brightness mean value sorting, the forensic algorithm efficiency can be effectively improved; and through comparing the similar brightness values of image blocks, the correctness is further improved and the image forensic efficiency is further improved. According to the method, the problem that the tampered images cannot be correctly detected due to cloning and tampering behaviors of large-scale zooming is solved; and through normalized image block brightness values, the detection result of cloned images with different brightness values is further improved.

Description

technical field [0001] The invention relates to the technical field of information security and information processing, in particular to a method for blind evidence collection of image tampering based on Sobel edge detection and image block brightness features. Background technique [0002] Image passive forensics technology, also known as image blind forensics technology, is a research field that has developed rapidly in recent years. It only uses the characteristics of the image itself to identify its authenticity, without any prior knowledge such as digital signatures or digital watermarks, and does not need to add watermark generation programs to camera equipment, so it has the advantage of a wide range of applications; at the same time , since there is no need to embed any information in the image, it will not reduce the image quality. When natural images are generated, they will be affected by factors such as the hardware and software inside the imaging device or the ...

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Problems solved by technology

Similar methods include the DWT-SVD method of Li et al., the DWT-DCT (QCD) method of Ghorbani et al., and Huang et al. proposed an improved method based on discrete cosine transform based on the algorithm of Fridrich et al. They introduced a threshold p to control the dimension of the feature vector of the image block. The above method can reduce the matching time by p% on average, but as the value of p increases, more and more feature dimensions are discarded, and the accuracy of the algorithm also decreased

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