{"title":"基于稀疏编码的纹理图像检索算法改进","authors":"Yansi Yang, Yingyun Yang, Xuan Zeng","doi":"10.1109/CyberC.2012.92","DOIUrl":null,"url":null,"abstract":"The demerits of the texture image retrieval algorithm based on sparse coding are found expression in the low recall and inconspicuous serial priority of qualified images. Several methods are presented in this paper to improve the performance of the image retrieval algorithm. Firstly, Brodatz texture image filter basis function is used for processing the texture images, thereafter, the kurtosis is added to generate the eigenvector, finally, the joint-scale filter basis is utilized to advance the filter effect. Experimental results indicate that the performance of the proposed methods is positive.","PeriodicalId":416468,"journal":{"name":"2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improvement of Texture Image Retrieval Algorithm Based on Sparse Coding\",\"authors\":\"Yansi Yang, Yingyun Yang, Xuan Zeng\",\"doi\":\"10.1109/CyberC.2012.92\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The demerits of the texture image retrieval algorithm based on sparse coding are found expression in the low recall and inconspicuous serial priority of qualified images. Several methods are presented in this paper to improve the performance of the image retrieval algorithm. Firstly, Brodatz texture image filter basis function is used for processing the texture images, thereafter, the kurtosis is added to generate the eigenvector, finally, the joint-scale filter basis is utilized to advance the filter effect. Experimental results indicate that the performance of the proposed methods is positive.\",\"PeriodicalId\":416468,\"journal\":{\"name\":\"2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CyberC.2012.92\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberC.2012.92","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improvement of Texture Image Retrieval Algorithm Based on Sparse Coding
The demerits of the texture image retrieval algorithm based on sparse coding are found expression in the low recall and inconspicuous serial priority of qualified images. Several methods are presented in this paper to improve the performance of the image retrieval algorithm. Firstly, Brodatz texture image filter basis function is used for processing the texture images, thereafter, the kurtosis is added to generate the eigenvector, finally, the joint-scale filter basis is utilized to advance the filter effect. Experimental results indicate that the performance of the proposed methods is positive.