| Geometrically robust image watermarking by sector-shaped partitioning of geometric-invariant regions. | |
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MedLine Citation:
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PMID: 19997427 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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In a feature-based geometrically robust watermarking system, it is a challenging task to detect geometric-invariant regions (GIRs) which can survive a broad range of image processing operations. Instead of commonly used Harris detector or Mexican hat wavelet method, a more robust corner detector named multi-scale curvature product (MSCP) is adopted to extract salient features in this paper. Based on such features, disk-like GIRs are found, which consists of three steps. First, robust edge contours are extracted. Then, MSCP is utilized to detect the centers for GIRs. Third, the characteristic scale selection is performed to calculate the radius of each GIR. A novel sector-shaped partitioning method for the GIRs is designed, which can divide a GIR into several sector discs with the help of the most important corner (MIC). The watermark message is then embedded bit by bit in each sector by using Quantization Index Modulation (QIM). The GIRs and the divided sector discs are invariant to geometric transforms, so the watermarking method inherently has high robustness against geometric attacks. Experimental results show that the scheme has a better robustness against various image processing operations including common processing attacks, affine transforms, cropping, and random bending attack (RBA) than the previous approaches. |
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Authors:
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Huawei Tian; Yao Zhao; Rongrong Ni; Gang Cao |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Optics express Volume: 17 ISSN: 1094-4087 ISO Abbreviation: Opt Express Publication Date: 2009 Nov |
Date Detail:
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Created Date: 2009-12-09 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101137103 Medline TA: Opt Express Country: United States |
Other Details:
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Languages: eng Pagination: 21819-36 Citation Subset: IM |
Affiliation:
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Institute of Information Science, Beijing Jiaotong University, Beijing, China. hwtian@live.cn |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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