Image Digital Watermarking Technique Based on Kernel Independent Component Analysis

  • Authors:

  • Yuancheng Li;Kehe Wu;Yinglong Ma;Shipeng Zhang

  • Affiliations:

  • School of Computer Science and Technology, North China Electric Power University, Beijing, 102206, China;School of Computer Science and Technology, North China Electric Power University, Beijing, 102206, China;School of Computer Science and Technology, North China Electric Power University, Beijing, 102206, China;School of Computer Science and Technology, North China Electric Power University, Beijing, 102206, China

  • Venue:
  • RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
  • Year:
  • 2009

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Abstract

In this paper, we present a novel image digital watermarking technique based on Kernel Independent Component Analysis (KICA). Use the nice characteristic of the KICA, which can results the blind separation of nonlinearly mixed signals, the imperceptibility and robustness requirements of watermarks are fulfilled and optimized. In the proposed scheme, the watermark image is first transformed by Arnold method, and then embedded into the lowest frequency subband in DWT domain. The recovery of owner's image is turning the watermarked image into DWT domains then use KICA to extract the watermark. Finally the watermark is transformed by Arnold method again, so we can get the original watermark image. Experimental results show that the proposed method gains better performance in robustness than that of ICA with respect to traditional image processing including cropping, filtering, add noise and JPEG image compression.