A Review on Ordered Dither Block Truncation Coding for Content Based Image Retrieval using Relevance Feedback [ ]

Now a days, content based image retrieval (CBIR) is the mainstay of the image retrieval systems. CBIR system is used in various areas like medical, academic, art, fashion, Entertainment .This project uses ordered-dither block truncation coding (ODBTC) for CBIR which have relevance feedback mechanism. In this project features of an image are extracted using ODBTC for the generation of image content descriptor. ODBTC offers a simple and effective descriptor to index images in CBIR system. ODBTC compresses an image block into minimum quantizer, maximum quantizer and bitmap image. The proposed image retrieval system generates two image features namely Color co-occurrence feature (CCF) and bit pattern feature (BPF) from the minimum quantizer, maximum quantizer and bitmap image respectively by involving the visual codebook. To be more profitable, relevance feedback technique can be applied into CBIR such that more precise results can be obtained by taking users feedback into account. The proposed method is superior to the block truncation coding image retrieval system and the other earlier method.