Erratum to: An improved block-based matching algorithm of copy-move forgery detection

Performance evaluation of block-based copy- move image forgery detection algorithms

Copy-move forgery is a particular type of distortion where a part or portions of one image is/are copied to other parts of the same image. This type of manipulation is done to hide a particular part of the image or to copy one or more objects into the same image. There are several methods for detecting copy-move forgery, including block-based and key point-based methods. In this paper, a method...

A Detection Algorithm for Image Copy-move Forgery Based on Improved Circular Projection Matching and PCA

Because general algorithms seldom detect copy-move forgery with angle rotation and block matching algorithms are very time-consuming, this paper proposes a detection algorithm which is able to detect copymove forgery with rotation of certain angles by using the direction invariance of the circular projection vector. At the same time, considering the influence of random noise and brightness chan...

Improved DSIFT Descriptor Based Copy-Rotate-Move Forgery Detection

In recent years, there has been a dramatic increase in the number of images captured by users. This is due to the wide availability of digital cameras and mobile phones which are able to capture and transmit images. Simultaneously, image-editing applications have become more usable, and a casual user can easily improve the quality of an image or change its content. The most common type of image...

Thinking beyond the block: block matching for copy-move forgery detection revisited

Copy-Move Forgery Detection by Matching Triangles of Keypoints

— Copy-move forgery is one of the most common types of tampering for digital images. Detection methods generally use block-matching approaches, which first divide the image into overlapping blocks and then extract and compare features to find similar ones, or point-based approaches, in which relevant keypoints are extracted and matched to each other to find similar areas. In this paper we prese...