Blur Detection of Digital Forgery Using Mathematical Morphology

  • Authors:

  • Linna Zhou;Dongming Wang;Yunbiao Guo;Jingfei Zhang

  • Affiliations:

  • Beijing University of Posts and Telecommunication, Beijing 100876, China and Beijing Application Institute of Electronic Technology, Beijing 100091, China;China Securities Regulatory Commission Information Center, Beijing 100032, China;Beijing Application Institute of Electronic Technology, Beijing 100091, China;Beijing Application Institute of Electronic Technology, Beijing 100091, China

  • Venue:
  • KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recent studies on agent techniques for digital content management have been focused on the guarantee of safety and intelligent management. The digital forensic to detect content tampering is a typical application of safety digital content management. Based on the edge processing and analysis using edge preserving smoothing filtering and mathematical morphology, a new blur edge detection scheme is proposed in this paper, which can indicate possible tampering and locate tampered regions without any embedded information such as watermarking technique. Experimental results demonstrate the effectiveness of the proposed scheme.