Two‐stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images

Abstract

ABSTRACT:In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods.

Subpixel corner point detecting method based on greyscale constraint used for calibrating industrial microscopic systems

“…Suppose the pixel coordinates of light heart in the image are represented as ( u 0 , v 0 ), and the physical size of every pixel in the x and y axes are d x and d y. The relation between the pixel coordinate system and world coordinates system is shown below: [16] where R stands for rotation matrix and T represents for translation matrix, f is the focal length of the microscope, ( X w , Y w , Z w ) presents the corner point coordinates of the checkerboard in the world coordinates, and ( u , v ) is subpixel corner point coordinates in the pixel coordinates system. Building equations by several points of checkerboard in pixel coordinates system and world coordinates system, the parameter matrixes of the system are solved by least‐square method, and then the calibrating process is finished.…”

“…This method analyses the matrix of local derivatives around each point. It has been deeply studied and improved by recent researcher [5, 13], for example, Liang et al [14], Banerjee et al [15], and Emam et al [16] present grey‐centre method based on Harris operator to implement subpixel corner point detecting. In this method, the location of corner points at pixel level are firstly solved by adopting Harris operator, and then in this location by building the error minimisation function and iterative solving it, the coordinates of subpixel corner points are attained, which has also higher detecting precision.…”

Image Authenticity Detection Using DWT and Circular Block-Based LTrP Features

“…However, the detection accuracy is low as compared to a simple SIFT-based approach. Emam et al [21] presented a novel method for CMFD that used the SIFT algorithm to extract the key features from the digital images texture area, and the Harris corner operator to measure the keypoints from the flat areas in the image. The keypoints from both descriptors were combined by using the Multi-support Region Order-based Gradient Histogram (MROGH) descriptor.…”

“…The forged content was computed by measuring the similarity of fused key features. The technique [21] is robust to additive noise attacks, however shows a low recall rate.…”

Extended Forgery Detection Framework for COVID-19 Medical Data Using Convolutional Neural Network

“…When the use of digital data increases, new software tools for manipulating photos and photographs are being implemented. These tools are used to make forged data, where objects can be added or deleted to look like real data [5]. Therefore, checking the validity of available digital content in the form of images has become crucial.…”