Keypoints-Based Image Passive Forensics Method for Copy-Move Attacks

Abstract

A novel image passive forensics method for copy-move forgery detection is proposed. The proposed method combines block matching technology and feature point matching technology, and breaks away from the general framework of the visual feature-based approach that used local visual feature such as SIFT and followed by a clustering procedure to group feature points that are spatially close. In our work, image keypoints are extracted using Harris detector, and the statistical features of keypoint neighborhoods are used to generate forensics features. Then we proposed a new forensics features matching approach, in which, a region growth technology and a mismatch checking approach are developed to reduce mismatched keypoints and improve detected accuracy. We also develop a duplicate region detection method based on the distance frequency of corresponding keypoint pairs. The proposed method can detect duplicate regions for high resolution images. It has higher detection accuracy and computation efficiency. Experimental results show that the proposed method is robust for content-preserving manipulations such as JPEG compression, gamma adjustment, filtering, luminance enhancement, blurring, etc.

A self-adaptive tampering detection algorithm based on image segmentation and feature point matching

“…This algorithm can resist rotation attacks and detect tampering in smooth areas, However, the algorithm complexity of this algorithm is relatively high. Reference [4] proposed a copy paste tamper detection algorithm based on Harris and DCT quantization coefficients. This algorithm first extracts the Harris points of the image to be tested, and then performs feature matching by the average DCT coefficient aty of the algorithm.…”

Blackman–Tukey spectral estimation and electric network frequency matching from power mains and speech recordings

“…Copy-move attacks tend to be very common in the field of image forensics. Efforts have been made to develop robust techniques for their detection [10][11][12]. A robust method employing discrete cosine transform and singular value decomposition in order to detect this kind of attacks was presented in [13].…”

Perceptual Hashing-Based Image Copy-Move Forgery Detection

“…Li et al in [14] try to reduce the similar region matching times and improve the DAR and FPR by segmenting a suspicious image into nonoverlapped patches. Wang et al in [15] introduced a keypoints-based image passive detecting method based on Harris detector and region growth technology. It is robust for JPEG compression, gamma adjustment, and luminance enhancement.…”