Journal Title : International Journal of Modern Trends in Engineering and Science


Author’s Name : R Rosilla parveen  unnamed

Volume 03 Issue 10 2016

ISSN no:  2348-3121

Page no: 90-92

Abstract – Recent works in this field offer algorithms that not only localize the tampering, but also recover the original content in the lost area. The self-restoration problem can be modeled as a source-channel coding problem. The original image is compressed using an efficient source en-coder. The output is then channel coded to be capable of tolerating a certain rate of tampering. At the receiver, de-coder reveals the encoder output bit stream if the tampering is below the certain limit. Decoder exploits the location of the erased blocks at the decoding, which are known thanks to the embedded check bits. The output of the source decoder is then used to replace the content of the tampered area. Watermarking the original images to protect them against tampering has recently attracted an overgrowing interest. The self-restoration problem from this general viewpoint, the performance is significantly improved comparing to the state of the art schemes, in terms of the quality of watermarked image, quality of the restored content, and tolerable tampering rate.   

Keywords— Channel Coding; Tamper Proof Images


  1. Shao-Hui Liu, Hong-Xun Yao, Wen Gao, and Yong-Liang Liu, “An image fragile watermark scheme basedon chaotic image pattern and pixel-pairs,” AppliedMathematics and Computation, vol. 185, no. 2, pp. 869– 882, 2007.
  2. Tien-You Lee and Shinfeng D. Lin, “Dual watermark forimage tamper detection and recovery,” Pattern Recogni-tion, vol. 41, no. 11, pp. 3497 – 3506, 2008.
  3. Xinpeng Zhang and Shuozhong Wang, “Fragile water-marking scheme using a hierarchical mechanism,” Sig-nal Processing, vol. 89, no. 4, pp. 675 – 679, 2009.
  4. Xinpeng Zhang, Shuozhong Wang, and Guorui Feng,“Fragile watermarking scheme with extensive contentrestoration capability,” in Digital Watermarking, vol.5703 of Lecture Notes in Computer Science, pp. 268–278. Springer Berlin Heidelberg, 2009.
  5. Chun-Wei Yang and Jau-Ji Shen, “Recover the tamperedimage based on vq indexing,” Signal Processing, vol.90, no. 1, pp. 331 – 343, 2010.
  6. Xinpeng Zhang, Shuozhong Wang, Zhenxing Qian, andGuorui Feng, “Reference sharing mechanism for water-mark self-embedding,” Image Processing, IEEE Trans-actions on, vol. 20, no. 2, pp. 485–495, 2011.
  7. Zhenxing Qian, Guorui Feng, Xinpeng Zhang, andShuozhong Wang, “Image self-embedding with high-quality restoration capability,” Digital Signal Process-ing, vol. 21, no. 2, pp. 278 – 286, 2011.
  8. P. Korus and A. Dziech, “Reconfigurable self-embedding with high quality restoration under exten-sive tampering,” in Image Processing (ICIP), 2012 19thIEEE International Conference on, 2012, pp. 2193–2196.
  9. Xinpeng Zhang, Zhenxing Qian, Yanli Ren, and GuoruiFeng, “Watermarking with flexible self-recovery qualitybased on compressive sensing and compositive reconstruction,” Information Forensics and Security, IEEE Transactions on, vol. 6, no. 4, pp. 1223–1232, 2011.
  10. P. Korus and A. Dziech, “Efficient method for contentreconstruction with self-embedding,” Image Processing,IEEE Transactions on, vol. 22, no. 3, pp. 1134–1147,2013.
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