{"product_id":"an-image-retrieval-with-color-and-texture-features-of-image-sub-blocks-von-kavitha-chaduvula","title":"An image retrieval with color and texture features of image sub-blocks","description":"\u003cp\u003eEach 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.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783639713244\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9783639713244","offer_id":39482486915165,"sku":"9783639713244","price":79.9,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/c1d43272-c6a2-4cbb-8ce9-889ad4d5795b.jpg?v=1758344754","url":"https:\/\/shop.autorenwelt.de\/products\/an-image-retrieval-with-color-and-texture-features-of-image-sub-blocks-von-kavitha-chaduvula","provider":"Autorenwelt Shop","version":"1.0","type":"link"}