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  • 标题:Combination of Local, Global and k-mean using Wavelet Transform for Content Base Image Retrieval
  • 本地全文:下载
  • 作者:Ekta Gupta ; Rajendra Singh Kushwah
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:6
  • 页码:253-266
  • DOI:10.14257/ijsip.2015.8.6.27
  • 出版社:SERSC
  • 摘要:In today's time, the requirement of content based image retrieval technique is more and more because of diverse areas such as Data Mining, Remote Sensing and Management of Earth Resources, , Crime Prevention, Weather forecasting, E-commerce, Medical Imaging. The proposed paper presents the content based image retrieval, using features like color and texture, called WBCHIR (Wavelet Based Color Histogram Image Retrieval).The shape and shade features are extracted in the course of wavelet transformation and color histogram and the arrangement of these features is vigorous to scaling and conversion of objects in an image. It is the first time to present segmentation and grid, feature extraction, K-means module and k-nearest neighbor clustering algorithms and bring in the neighborhood module to build the CBIR system. It is the hybrid method of global and local features with k-means clustering algorithm
  • 关键词:CBIR; K-means; DWT; Global Feature
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