吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (4): 1232-1238.doi: 10.13229/j.cnki.jdxbgxb201604032

• Orginal Article • Previous Articles     Next Articles

Image tampering assessment model based on statistical features

SHEN Xuan-jing1, 2, FAN Zi-long1, 2, LYU Ying-da3, CHEN Hai-peng1, 2   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;
    3.Public Computer Teaching and Research Center Technology, Jilin University, Changchun 130012, China
  • Received:2014-12-05 Online:2016-07-20 Published:2016-07-20

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Abstract: In order to qualitatively analyze different tampering means of digital images, a tampering evaluation model based on image statistical features is proposed. First, the Local Ternary Pattern (LTP) features, Local Binary Pattern (LBP) features and Weber Local Descriptor (WLD) features ternary are extracted from the image. Then, SVM is used to classify the nature images, computer generated images, copy-pasted images, spliced images and recaptured images. Experimental results show that the proposed model can effectively classify the tampering images in the blind environment, objectively identify the image tampering method, and the comprehensive correct detection rate can reach 85%.

Key words: computer application, blind identification, tampering evaluation model, LTP feature vector, LBP feature vector, WLD feature vector

CLC Number: 

  • TP391
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