Region duplication detection based on Harris corner points and step sector statistics

  • Authors:
  • Likai Chen;Wei Lu;Jiangqun Ni;Wei Sun;Jiwu Huang

  • Affiliations:
  • School of Information Science and Technology, Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou 510006, China;School of Information Science and Technology, Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou 510006, China;School of Information Science and Technology, Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou 510006, China;School of Software, Sun Yat-sen University, Guangzhou 510006, China;School of Information Science and Technology, Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou 510006, China

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Region duplication is a simple and effective operation for digital image forgeries. The detection of region duplication is very important in digital image forensics. Most existing detection methods for region duplication are based on exhaustive block-matching of image pixels or transform coefficients. They may not be effective when the duplicate regions have gone through some geometrical transformations. In this paper, a novel region duplication detection method that is robust to general geometrical transformations is proposed. Firstly, the Harris corner interest points in an image are detected. Then, an image region description method based on step sector statistics is developed to represent the small circle image region around each Harris point with a feature vector. Finally, the small circle image regions are matched using the best-bin-first algorithm to reveal duplicate regions. Experimental results show that the proposed method can work effectively on the forged images from two image databases, and it is also robust to several geometrical transformations and image degradations.