Fine-grained image splicing area detection method

Abstract

The invention discloses a fine-grained image splicing region detection method, which comprises the following steps of: firstly, extracting RGB (Red, Green and Blue) color channels of an image, establishing a linear interpolation model, and respectively estimating interpolation coefficients of the three channels through a covariance matrix so as to reconstruct the three channels; and then, constructing an image forensic feature by using a Laplace operator, performing binarization processing and morphological operation on the forensic feature, performing non-overlapping blocking on a coarse-grained detection result, extracting texture strength features of coarse-grained blocks, and then performing classification and false detection removal to obtain a detection result of a fine-grained splicing region; and finally, smoothing the edge of the detection result of the fine-grained splicing region through a super-pixel segmentation algorithm to obtain a final detection result of the image splicing region. According to the method, the problem that a common CFA-based image stitching detection method is not robust to JPEG compression is solved.

Description

technical field [0001] The invention belongs to the technical field of image tampering detection, and in particular relates to a fine-grained image splicing region detection method. Background technique [0002] With the rapid development of digital technology and the widespread use of various powerful digital image editing tools, non-professionals can easily beautify, edit, or even tamper and forge digital images, which will destroy the authenticity and integrity of image content. sex and originality. In recent years, many falsified images have been used in scientific research, news media, judicial forensics, finance, military and other fields, seriously affecting the credibility of image content and causing serious negative effects in many fields. [0003] Image content tampering includes heterogeneous image splicing / compositing, homologous image Copy-Move attack, and image local property change. Image stitching / synthesis technology refers to splicing parts of an image t...

AI Technical Summary

Problems solved by technology

[0026] The purpose of the present invention is to provide a fine-grained image stitching area detection method, which solves the problems of low precision such as missed detection and large false detection area in the prior art, and the problem of failure to detect the target area; Dependency of extraction or image segmentation algorithms and solves the problem of poor robustness of existing techniques

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