Electronic Science and Technology ›› 2020, Vol. 33 ›› Issue (12): 49-53.doi: 10.16180/j.cnki.issn1007-7820.2020.12.010

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Image Splicing Detection Based on Optimal Color Channel

XIONG Shiting,ZHANG Yujin,LIU Tingting,FANG Xiangyu   

  1. School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China
  • Received:2019-09-08 Online:2020-12-15 Published:2020-12-22
  • Supported by:
    fund:Natural Science Foundation of Shanghai(17ZR1411900);The Post-Graduation Innovation Project of Shanghai University of Engineering Science(18KY0208)


In view of the problem that different color channels have effect on the noise estimation value, an image splicing detection method based on optimal color channel is proposed. The noise on the optimal color channel is estimated by principal component analysis and the method of K-means clustering is used to cluster according to the noise value. The clustering result is divided into suspicious part and non-suspicious part. The two-phase strategy can further locate the tampering area. The method is effective when the noise value difference between the original area and the splicing area was large or small, and the splicing area can be located. Experiments show that compared with the existing methods, the proposed method achieves good detection results, and the performance is better.

Key words: image splicing detection, principal component analysis, optimal color channel, K-means, splicing localization, noise estimation

CLC Number: 

  • TP391.9