Multimedia Tools and Applications

, Volume 75, Issue 17, pp 10201–10211 | Cite as

Image tamper detection based on noise estimation and lacunarity texture

Article

Abstract

Aiming at the problem of image tampering, a novel detection method is proposed based on the image noise and lacunarity. As there exist differences in image sensor pattern noise and image lacunarity between real image and tampered image, standard deviation of noise, relative frequency lacunarity (RFL), relative frequency mean (RFM) and relative frequency variance (RFV) are extracted from the suspected image to construct feature space. By using LIBSVM classifier, the image is detected if it is tampered or not. Experimental results and analysis show that it can effectively be used for the detection of real image and tampered image, natural image and computer generated graphics. Furthermore, it can be implemented for the detection of artificial blurring in the image with high precision.

Keywords

Digital image forensics Sensor pattern noise Image tamper Lacunarity 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Qiuwei Yang
    • 1
  • Fei Peng
    • 1
    • 2
  • Jiao-Ting Li
    • 1
  • Min Long
    • 3
  1. 1.School of Computer Science and Electronic EngineeringHunan UniversityChangshaChina
  2. 2.School of Computer and SoftwareNanjing University of Information Science & TechnologyNanjingChina
  3. 3.College of Computer and Communication EngineeringChangsha University of Science and TechnologyChangshaChina

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