• 제목/요약/키워드: Image Authentication and Self-recovery

검색결과 2건 처리시간 0.016초

Review on Self-embedding Fragile Watermarking for Image Authentication and Self-recovery

  • Wang, Chengyou;Zhang, Heng;Zhou, Xiao
    • Journal of Information Processing Systems
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    • 제14권2호
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    • pp.510-522
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    • 2018
  • As the major source of information, digital images play an indispensable role in our lives. However, with the development of image processing techniques, people can optionally retouch or even forge an image by using image processing software. Therefore, the authenticity and integrity of digital images are facing severe challenge. To resolve this issue, the fragile watermarking schemes for image authentication have been proposed. According to different purposes, the fragile watermarking can be divided into two categories: fragile watermarking for tamper localization and fragile watermarking with recovery ability. The fragile watermarking for image tamper localization can only identify and locate the tampered regions, but it cannot further restore the modified regions. In some cases, image recovery for tampered regions is very essential. Generally, the fragile watermarking for image authentication and recovery includes three procedures: watermark generation and embedding, tamper localization, and image self-recovery. In this article, we make a review on self-embedding fragile watermarking methods. The basic model and the evaluation indexes of this watermarking scheme are presented in this paper. Some related works proposed in recent years and their advantages and disadvantages are described in detail to help the future research in this field. Based on the analysis, we give the future research prospects and suggestions in the end.

Region-based scalable self-recovery for salient-object images

  • Daneshmandpour, Navid;Danyali, Habibollah;Helfroush, Mohammad Sadegh
    • ETRI Journal
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    • 제43권1호
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    • pp.109-119
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    • 2021
  • Self-recovery is a tamper-detection and image recovery methods based on data hiding. It generates two types of data and embeds them into the original image: authentication data for tamper detection and reference data for image recovery. In this paper, a region-based scalable self-recovery (RSS) method is proposed for salient-object images. As the images consist of two main regions, the region of interest (ROI) and the region of non-interest (RONI), the proposed method is aimed at achieving higher reconstruction quality for the ROI. Moreover, tamper tolerability is improved by using scalable recovery. In the RSS method, separate reference data are generated for the ROI and RONI. Initially, two compressed bitstreams at different rates are generated using the embedded zero-block coding source encoder. Subsequently, each bitstream is divided into several parts, which are protected through various redundancy rates, using the Reed-Solomon channel encoder. The proposed method is tested on 10 000 salient-object images from the MSRA database. The results show that the RSS method, compared to related methods, improves reconstruction quality and tamper tolerability by approximately 30% and 15%, respectively.