基于纹理分割的半脆弱水印算法

Sheng-bing Che, Hanxu Gao, Jin Luo
{"title":"基于纹理分割的半脆弱水印算法","authors":"Sheng-bing Che, Hanxu Gao, Jin Luo","doi":"10.1109/ICWAPR.2010.5576433","DOIUrl":null,"url":null,"abstract":"Based on texture visual features, region segmentation operator and quantization step equations were put forward. This guarantees the transparency of carrier image and the robustness of watermarking image extracted. After segmentation, the texture contour was clear, and the segmented results of smooth and texture region were satisfying. And it brought up the pixel value adjustment operator of IDWT. The basic idea of the algorithm is that after discrete wavelet transform, divided the low frequency coefficients LL into 2×2 blocks, then defined block coefficient suni ∑. If the value of ∑ was greater than the threshold, the block was segmented into texture area, or segmented into smooth area. When quantifying the step, the intensity and texture coefficient were considered, which made the transparency and robustness optimal. Experimental results showed that the result of texture segmentation was obviously better than the present algorithms. The pixel value could be adjusted by coefficient adjustment operator exactly. The carrier image had not only good transparency, but also better anti-attack capability.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"194 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Semi-fragilewatermarking algorithm based on texture segmentation\",\"authors\":\"Sheng-bing Che, Hanxu Gao, Jin Luo\",\"doi\":\"10.1109/ICWAPR.2010.5576433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on texture visual features, region segmentation operator and quantization step equations were put forward. This guarantees the transparency of carrier image and the robustness of watermarking image extracted. After segmentation, the texture contour was clear, and the segmented results of smooth and texture region were satisfying. And it brought up the pixel value adjustment operator of IDWT. The basic idea of the algorithm is that after discrete wavelet transform, divided the low frequency coefficients LL into 2×2 blocks, then defined block coefficient suni ∑. If the value of ∑ was greater than the threshold, the block was segmented into texture area, or segmented into smooth area. When quantifying the step, the intensity and texture coefficient were considered, which made the transparency and robustness optimal. Experimental results showed that the result of texture segmentation was obviously better than the present algorithms. The pixel value could be adjusted by coefficient adjustment operator exactly. The carrier image had not only good transparency, but also better anti-attack capability.\",\"PeriodicalId\":219884,\"journal\":{\"name\":\"2010 International Conference on Wavelet Analysis and Pattern Recognition\",\"volume\":\"194 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Wavelet Analysis and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWAPR.2010.5576433\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2010.5576433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

基于纹理视觉特征,提出了区域分割算子和量化步进方程。这保证了载体图像的透明性和水印图像提取的鲁棒性。分割后的纹理轮廓清晰,光滑区域和纹理区域的分割结果令人满意。提出了IDWT的像素值调整算子。该算法的基本思想是经过离散小波变换后,将低频系数LL分成2×2块,然后定义块系数suni∑。如果∑值大于阈值,则将块分割为纹理区域,或分割为光滑区域。在量化步骤时,考虑了强度和纹理系数,使透明度和鲁棒性达到最优。实验结果表明,该算法的纹理分割效果明显优于现有算法。通过系数调整算子可以精确地调整像素值。该载体图像不仅具有良好的透明性,而且具有较好的抗攻击能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semi-fragilewatermarking algorithm based on texture segmentation
Based on texture visual features, region segmentation operator and quantization step equations were put forward. This guarantees the transparency of carrier image and the robustness of watermarking image extracted. After segmentation, the texture contour was clear, and the segmented results of smooth and texture region were satisfying. And it brought up the pixel value adjustment operator of IDWT. The basic idea of the algorithm is that after discrete wavelet transform, divided the low frequency coefficients LL into 2×2 blocks, then defined block coefficient suni ∑. If the value of ∑ was greater than the threshold, the block was segmented into texture area, or segmented into smooth area. When quantifying the step, the intensity and texture coefficient were considered, which made the transparency and robustness optimal. Experimental results showed that the result of texture segmentation was obviously better than the present algorithms. The pixel value could be adjusted by coefficient adjustment operator exactly. The carrier image had not only good transparency, but also better anti-attack capability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信