Parallel Image Forgery Detection Using FREAK Descriptor

  • M. SrideviEmail author
  • S. AishwaryaEmail author
  • Amedapu NidheeshaEmail author
  • Divyansh BokadiaEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 107)


Nowadays, a large amount of information is being exchanged in the form of images. This information can be tampered easily through a process called forging. This paper focuses on detection of copy-move image forgery in an image. To implement it in a faster way, parallel copy-move image forgery is proposed. The features from accelerated segment test (FAST) method is applied to detect the key points of the input image. After detection of keypoints, fast retina keypoint (FREAK) binary descriptor method is used to find the features of these keypoints. These features are then matched, and the correlation factor is found to detect image forgery. The image is split into various regions, and detection in each region is done in parallel. Hence, it helps to find out the image forgery in a faster way. The analysis shows that the proposed method is performed in a faster manner to detect the forged region.


Image forgery detection Copy-move forgery Correlation Matching features Parallelism 


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNational Institute of Technology, TiruchirappalliTiruchirappalliIndia

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