Abstract
Region duplication forgery detection is a special type of forgery detection approach and widely used research topic under digital image forensics. In copy move forgery, a specific area is copied and then pasted into any other region of the image. Due to the availability of sophisticated image processing tools, it becomes very hard to detect forgery with naked eyes. From the forged region of an image no visual clues are often detected. For making the tampering more robust, various transformations like scaling, rotation, illumination changes, JPEG compression, noise addition, gamma correction, and blurring are applied. So there is a need for a method which performs efficiently in the presence of all such attacks. This paper presents a detection method based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC). SURF detects the keypoints and their corresponding features. From these sets of keypoints, grouping is performed on the matched keypoints by HAC that shows copied and pasted regions.
Highlights
Today, the use of digital images is increasing rapidly in almost every area of human life like in education, software companies, television, businesses, journalism, medical imaging, and social media
The performance of detection method is measured in terms of true positive rate (TPR), false positive rate (FPR), and time complexity where images detected as forged being forged total number of forged images
A method was presented for detecting the duplicate region based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC)
Summary
The use of digital images is increasing rapidly in almost every area of human life like in education, software companies, television, businesses, journalism, medical imaging, and social media. It is easy to learn and understand anything visually rather than only reading or listening. Another aspect is that generally visual information is believed to be true. As the technology advances and lots of sophisticated image processing tools are available, it becomes very easy to edit visual information. Some of the tools are Adobe Photoshop, GIMP, Macromedia Freehand, and Corel Paint Shop [1, 2]. A big question arises, how to distinguish the photographic images from the photorealistic ones [3]
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