{"title":"A ridgelet representation of semantic object using watershed segmentation","authors":"M. Hasegawa, S. Tajima","doi":"10.3169/ITEJ.59.786","DOIUrl":null,"url":null,"abstract":"We propose an application of the ridgelet transform to semantic objects which are produced by the watershed segmentation. The ridgelet transform is effective in representing line singularities; therefore, it is a powerful tool for coding. Moreover, it has the advantageous property of rotating a block easily by shifting coefficients in ridgelet domain. Nevertheless, the rotating target is not a rectangular block but a real object. For that reason, we divide a picture into semantic objects using the watershed segmentation, and each object is converted by the ridgelet transform; then, we can rotate each object easily. Predictive coding with this method is attempted. Simulations show that referencing object with rotation is very effective in prediction.","PeriodicalId":237047,"journal":{"name":"IEEE International Symposium on Communications and Information Technology, 2004. ISCIT 2004.","volume":"14 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Symposium on Communications and Information Technology, 2004. ISCIT 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3169/ITEJ.59.786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We propose an application of the ridgelet transform to semantic objects which are produced by the watershed segmentation. The ridgelet transform is effective in representing line singularities; therefore, it is a powerful tool for coding. Moreover, it has the advantageous property of rotating a block easily by shifting coefficients in ridgelet domain. Nevertheless, the rotating target is not a rectangular block but a real object. For that reason, we divide a picture into semantic objects using the watershed segmentation, and each object is converted by the ridgelet transform; then, we can rotate each object easily. Predictive coding with this method is attempted. Simulations show that referencing object with rotation is very effective in prediction.