中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Optimized Local Image Watermarking Combining Feature Point and Texture

文献类型:会议论文

作者Ying Huang1; Hu Guan1; Shuwu Zhang1; Baoning Niu2
出版日期2020-10
会议日期October 30-31, 2020
会议地点Beijing, China
国家中国
英文摘要

The textured regions embedded a watermark have better visual quality than the smooth regions in an image. To take advantage of the image texture being easy to hide the watermark, accurately locating the regions in an image with rich texture is significant. This paper proposes an optimized local image watermarking algorithm combining feature point and texture. The SURF feature points extracted from an image with moderate scales are selected to obtain initial watermark embedding regions. A scoring scheme by comprehensively analyzing texture, scale, and position of a region is proposed to evaluate the regions around each initial embedding region, and select the regions with the highest score from them to constitute the candidate embedding regions. Finally, the same watermarks are embedded in multiple non-overlapping embedding regions to guarantee the imperceptibility and improve the robustness. The simulation experiments on 100 images show the superiority of our proposed method compared with the state-of-the-art method in terms of imperceptibility and robustness.

源文献作者中国传媒大学,中国科学院自动化研究所
产权排序1
语种英语
源URL[http://ir.ia.ac.cn/handle/173211/47502]  
专题数字内容技术与服务研究中心_新媒体服务与管理技术
通讯作者Ying Huang
作者单位1.Institute of Automation, Chinese Academy of Sciences
2.Taiyuan University of Technology
推荐引用方式
GB/T 7714
Ying Huang,Hu Guan,Shuwu Zhang,et al. Optimized Local Image Watermarking Combining Feature Point and Texture[C]. 见:. Beijing, China. October 30-31, 2020.

入库方式: OAI收割

来源:自动化研究所

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