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Multimedia Tools and Applications

, Volume 76, Issue 24, pp 26503–26522 | Cite as

An efficiency enhanced cluster expanding block algorithm for copy-move forgery detection

  • Chien-Chang Chen
  • Han Wang
  • Cheng-Shian Lin
Article

Abstract

The proposed scheme detects the copy-move forgery detection regions through the invariant features extracted from each block. First, an image is divided into overlapping blocks, and seven invariant moments of the maximum circle area in each block are calculated as moment features. Two clustering features, denoted by mean and variance of these seven moment features, are acquired for block comparison to reduce computation time. Therefore, the proposed scheme takes limited computation time because the seven moment features in each block are only compared to other blocks under the intersection of closed mean and variance features. The copy-move forgery regions can be found by matching the detected blocks with relative distance calculation. Experimental results show that the adopted moment features are efficient for detecting rotational or flipped duplicated regions.

Keywords

Forgery duplication Invariant moment Mean Variance Clustering 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Computer Science and Information EngineeringTamkang UniversityNew Taipei CityRepublic of China
  2. 2.Department of Business AdministrationCTBC Financial Management CollegeTainanRepublic of China

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