{"product_id":"image-retrieval-with-color-and-texture-features-of-image-sub-blocks","title":"image retrieval with color and texture features of image sub-blocks","description":"Each image is partitioned into 4×6 grids of equal-sized sub-blocks. The size of the sub-block is maintained as 64x64 pixels. Further the size of the sub-block is fixed for all the images. Then the color and texture features of each sub-block are computed. A color feature descriptor Local AutoCorrelogram (LAC) which is invariant to translation and occlusion is proposed to represent the color of the sub-block. Similarly, the texture of the sub-block is extracted based on Edge Oriented Gray Tone Spatial Dependency Matrix (EOGTSDM) of an image. An image matching scheme based on Integrated Minimum Cost Sub-block Matching (IMCSM) principle is used to compare the query and the target image, which in turn reduces the cost of finding the integrated matching distance. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image, which is used for matching the images. To further improve the quality of retrieval, a Relevance Feedback approach based on a feature re-weighting scheme is used to improve the retrieval accuracy. The experimental results show that this method has improved retrieval precision and recall.","brand":"Scholars' Press","offers":[{"title":"Default Title","offer_id":47121011015732,"sku":"9783639713244","price":86.29,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0699\/8638\/5972\/files\/imageloader_5e501d5b-060e-4890-a29a-c01231a00ce4.jpg?v=1758813161","url":"https:\/\/worldcaribbeanbooks.com\/products\/image-retrieval-with-color-and-texture-features-of-image-sub-blocks","provider":"World Caribbean Books","version":"1.0","type":"link"}