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文章基本信息

  • 标题:Comparision Of Traditional Method of Histogram Equalisation with HSV and Kekre Transform for Content Based Image Retrieval
  • 本地全文:下载
  • 作者:Ms. Venu Shah ; Ms. Archana Choudhary ; Prof. Kavita Tewari
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2011
  • 卷号:3
  • 期号:7
  • 页码:2712-2718
  • 出版社:Engg Journals Publications
  • 摘要:Content-based image retrieval system based on an efficient combination of both colours and features is explained in this paper. According to Kekre�s Transform, feature vectors are formed using acombination of row mean and column mean of both query as well as database images, to measure the extent of similarity using Euclidian distance. Similarly, HSV colour space quantifies the colour space intodifferent regions and thereby calculating its mean and Euclidian distance the colour vector can be derived. Taking mean of the Euclidian distances of both the algorithms better accuracy of the image retrieval process can be attained.
  • 关键词:CBIR; Histogram equalisation; HSV segmentation
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