A novel method for detecting image sharpening based on local binary pattern

Feng Ding, Guopu Zhu, Yun Qing Shi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

In image forensics, determining the image editing history plays an important role as most digital images need to be edited for various purposes. Image sharpening which aims to enhance the image edge contrast for a clear view is considered to be one of the most fundamental editing techniques. However, only a few works have been reported on the detection of image sharpening. From a perspective of texture analysis, the over-shoot artifact caused by image sharpening can be regarded as a special kind of texture modification. We also find that this kind of texture modification can be characterized by local binary patterns (LBP), which is one of the most wildly used methods for texture classification. Therefore, in this paper we propose a novel method based on LBP to detect the application of sharpening in digital image. At first, we employ Canny operator for edge detection. The rotation-invariant LBP was applied to the detected edge pixels of images for feature extraction. Then features extracted from sharpened and unsharpened images are fed into a support vector machine (SVM) classifier for classification. Experimental results on digital images with different coefficients for sharpening have demonstrated the capability of this method. Comparing with the state-of-arts, the proposed method is validated to be the one with better performance in sharpening detection.

Original languageEnglish (US)
Title of host publicationDigital-Forensics and Watermarking - 12th International Workshop, IWDW 2013, Revised Selected Papers
PublisherSpringer Verlag
Pages180-191
Number of pages12
ISBN (Print)9783662438855
DOIs
StatePublished - 2014
Event12th International Workshop on Digital-Forensics and Watermarking, IWDW 2013 - Auckland, New Zealand
Duration: Oct 1 2013Oct 4 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8389 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Workshop on Digital-Forensics and Watermarking, IWDW 2013
Country/TerritoryNew Zealand
CityAuckland
Period10/1/1310/4/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Keywords

  • Digital forensics
  • LBP
  • Rotation invariant
  • Sharpen
  • Sharpening detection
  • Texture

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