{"title":"One-dimensional Color-level Co-occurrence matrices","authors":"M. Benco, R. Hudec, S. Matuska, M. Zachariasova","doi":"10.1109/ELEKTRO.2012.6225600","DOIUrl":null,"url":null,"abstract":"The texture feature extraction plays important role in image analysis. This paper deals with improvement of the one-dimensional version of GLCM (Gray Level Cooccurrence Matrix). In our approach, the color information of texture was taken into consideration. The novel One dimensional Color Level Co-occurrence Matrix (1D-CLCM) are designed. Performances of proposed method are verified on database of 2600 color images. Experimental results demonstrated that 1D-CLCM is more effective compared to one-dimensional and original GLCM for image retrieval.","PeriodicalId":343071,"journal":{"name":"2012 ELEKTRO","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 ELEKTRO","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELEKTRO.2012.6225600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The texture feature extraction plays important role in image analysis. This paper deals with improvement of the one-dimensional version of GLCM (Gray Level Cooccurrence Matrix). In our approach, the color information of texture was taken into consideration. The novel One dimensional Color Level Co-occurrence Matrix (1D-CLCM) are designed. Performances of proposed method are verified on database of 2600 color images. Experimental results demonstrated that 1D-CLCM is more effective compared to one-dimensional and original GLCM for image retrieval.
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