Copy-Move Detection Using Gray Level Run Length Matrix Features

  • Saba MushtaqEmail author
  • Ajaz Hussain Mir
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 472)


Copy-move detection is a well-recognized and active area of research owing to great demand of authenticating genuineness of images. Currently, available techniques for copy-move detection fail to accurately locate the tampered region and lack robustness against common post-processing operations like compression, blurring, and brightness changes. This paper proposes a novel technique for the detection and localization of copy-move regions in image using gray level run length matrix (GLRLM) features. In the proposed method, we first divide the forged image into overlapping blocks and GLRLM features are calculated for each block. Features calculated for each block form feature vectors. Feature vectors thus obtained are lexicographically sorted. Blocks with similar features are identified using Euclidean feature distances. Post-processing isolates similar blocks. Results demonstrate the effectiveness of the proposed scheme to locate copy-move forgery and robustness against operations like JPEG compression, blurring, and contrast adjustments.


Copy-move Region duplication Image forgery detection Image texture GLRLM 


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringNational Institute of Technology SrinagarSrinagarIndia

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