期刊名称：International Journal of Managing Information Technology
印刷版ISSN：0975-5926
电子版ISSN：0975-5586
出版年度：2011
卷号：3
期号：2
DOI：10.5121/ijmit.2011.32029
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Content-based image retrieval (CBIR) systems utilize low level query image feature as identifying similarity between a query image and the image database. Image contents are plays significant role for image retrieval. There are three fundamental bases for content-based image retrieval, i.e. visual feature extraction, multidimensional indexing, and retrieval system design. Each image has three contents such as: color, texture and shape features. Color and texture both plays important image visual features used in Content-Based Image Retrieval to improve results. Color histogram and texture features have potential to retrieve similar images on the basis of their properties. As the feature extracted from a query is low level, it is extremely difficult for user to provide an appropriate example in based query. To overcome these problems and reach higher accuracy in CBIR system, providing user with relevance feedback is famous for provide promising solution
关键词：Content-based image retrieval; Color Histogram; Relevance Feedback; k-means
