{"title":"一种基于颜色矩与Gabor滤波器相结合的新型CBIR系统","authors":"Muhsina Kaipravan, R. Rejiram","doi":"10.1109/SAPIENCE.2016.7684169","DOIUrl":null,"url":null,"abstract":"Content based image retrieval (CBIR) systems use the contents of image such as color, texture and shape to represent and retrieve images from large databases. In this paper, we present a CBIR system based on integration of both color and texture feature. Due to the poor discriminating power of color histogram, color moments that encode some spatial information are used to extract the color feature from the image. Gabor filter is used to represent the texture feature. Then we assign weights to each feature and calculate the similarity of combined features using Manhattan distance measure. A comparison study of the proposed method with other conventional method is also presented in this paper and experimental results show that the proposed method has higher retrieval accuracy.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"A novel CBIR system based on combination of color moment and Gabor filter\",\"authors\":\"Muhsina Kaipravan, R. Rejiram\",\"doi\":\"10.1109/SAPIENCE.2016.7684169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Content based image retrieval (CBIR) systems use the contents of image such as color, texture and shape to represent and retrieve images from large databases. In this paper, we present a CBIR system based on integration of both color and texture feature. Due to the poor discriminating power of color histogram, color moments that encode some spatial information are used to extract the color feature from the image. Gabor filter is used to represent the texture feature. Then we assign weights to each feature and calculate the similarity of combined features using Manhattan distance measure. A comparison study of the proposed method with other conventional method is also presented in this paper and experimental results show that the proposed method has higher retrieval accuracy.\",\"PeriodicalId\":340137,\"journal\":{\"name\":\"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAPIENCE.2016.7684169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAPIENCE.2016.7684169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel CBIR system based on combination of color moment and Gabor filter
Content based image retrieval (CBIR) systems use the contents of image such as color, texture and shape to represent and retrieve images from large databases. In this paper, we present a CBIR system based on integration of both color and texture feature. Due to the poor discriminating power of color histogram, color moments that encode some spatial information are used to extract the color feature from the image. Gabor filter is used to represent the texture feature. Then we assign weights to each feature and calculate the similarity of combined features using Manhattan distance measure. A comparison study of the proposed method with other conventional method is also presented in this paper and experimental results show that the proposed method has higher retrieval accuracy.