{"title":"基于图像纹理分析的小波域自适应数据隐藏","authors":"Yuanyuan Wang, Yibiao Yu","doi":"10.1109/ICALIP.2008.4590210","DOIUrl":null,"url":null,"abstract":"According to texture analysis in low frequency sub-band of DWT, an adaptive image hiding algorithm is proposed. The low-frequency part of DWT is classified as smooth, edge and texture region by entropy and standard deviation, and different regions are assigned with different hiding bits, which will increase the hiding capacity. The blind detection is accomplished by resetting low bits in DWT low-frequency regions. Experimental results show the embedding rate of image with complex texture can be increased up to 13.89%. The proposed method is quite effective and robust to attacks.","PeriodicalId":175885,"journal":{"name":"2008 International Conference on Audio, Language and Image Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An adaptive data hiding in wavelet domain based on texture analysis of image\",\"authors\":\"Yuanyuan Wang, Yibiao Yu\",\"doi\":\"10.1109/ICALIP.2008.4590210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to texture analysis in low frequency sub-band of DWT, an adaptive image hiding algorithm is proposed. The low-frequency part of DWT is classified as smooth, edge and texture region by entropy and standard deviation, and different regions are assigned with different hiding bits, which will increase the hiding capacity. The blind detection is accomplished by resetting low bits in DWT low-frequency regions. Experimental results show the embedding rate of image with complex texture can be increased up to 13.89%. The proposed method is quite effective and robust to attacks.\",\"PeriodicalId\":175885,\"journal\":{\"name\":\"2008 International Conference on Audio, Language and Image Processing\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Audio, Language and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICALIP.2008.4590210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Audio, Language and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALIP.2008.4590210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An adaptive data hiding in wavelet domain based on texture analysis of image
According to texture analysis in low frequency sub-band of DWT, an adaptive image hiding algorithm is proposed. The low-frequency part of DWT is classified as smooth, edge and texture region by entropy and standard deviation, and different regions are assigned with different hiding bits, which will increase the hiding capacity. The blind detection is accomplished by resetting low bits in DWT low-frequency regions. Experimental results show the embedding rate of image with complex texture can be increased up to 13.89%. The proposed method is quite effective and robust to attacks.