Image retrieval based on indexing and relevance feedback

@article{citeulike:976843, abstract = {In content based image retrieval (CBIR) system, search engine retrieves the images similar to the query image according to a similarity measure. It should be fast enough and must have a high precision of retrieval. Indexing scheme is used to achieve a fast response and relevance feedback helps in improving the retrieval precision. In this paper, a human perception based similarity measure is presented and based on it a simple yet novel indexing scheme with relevance feedback is discussed. The indexing scheme is designed based on the primary and secondary keys which are selected by analysing the entropy of features. A relevance feedback method is proposed based on Mann-Whitney test. The test is used to identify the discriminating features from the relevant and irrelevant images in a retrieved set. Then emphasis of the discriminating features are updated to improve the retrieval performance. The relevance feedback scheme is implemented for two different similarity measure (Euclidean distance based and human perception based). The experiment justifies the effectiveness of the proposed methodologies. Finally, the indexing scheme and relevance feedback mechanism are combined to build up the search engine.}, author = {Saha, Sanjoy K. and Das, Amit K. and Chanda, Bhabatosh }, booktitle = {Advances in Visual information Processing, Special Issue of Pattern Recognition Letters on Advances in Visual Information Processing. (ICVGIP 2004)}, citeulike-article-id = {976843}, doi = {http://dx.doi.org/10.1016/j.patrec.2006.04.005}, journal = {Pattern Recognition Letters}, keywords = {content\_based\_retrieval, image\_retrieval}, month = {February}, number = {3}, pages = {357--366}, posted-at = {2006-12-06 14:42:12}, priority = {2}, title = {Image retrieval based on indexing and relevance feedback}, url = {http://dx.doi.org/10.1016/j.patrec.2006.04.005}, volume = {28}, year = {2007} }

TY - JOUR ID - citeulike:976843 L3 - citeulike-article-id:976843 TI - Image retrieval based on indexing and relevance feedback T2 - Advances in Visual information Processing, Special Issue of Pattern Recognition Letters on Advances in Visual Information Processing. (ICVGIP 2004) JF - Pattern Recognition Letters VL - 28 IS - 3 SP - 357 EP - 366 N2 - In content based image retrieval (CBIR) system, search engine retrieves the images similar to the query image according to a similarity measure. It should be fast enough and must have a high precision of retrieval. Indexing scheme is used to achieve a fast response and relevance feedback helps in improving the retrieval precision. In this paper, a human perception based similarity measure is presented and based on it a simple yet novel indexing scheme with relevance feedback is discussed. The indexing scheme is designed based on the primary and secondary keys which are selected by analysing the entropy of features. A relevance feedback method is proposed based on Mann-Whitney test. The test is used to identify the discriminating features from the relevant and irrelevant images in a retrieved set. Then emphasis of the discriminating features are updated to improve the retrieval performance. The relevance feedback scheme is implemented for two different similarity measure (Euclidean distance based and human perception based). The experiment justifies the effectiveness of the proposed methodologies. Finally, the indexing scheme and relevance feedback mechanism are combined to build up the search engine. KW - content_based_retrieval KW - image_retrieval AU - Saha, Sanjoy AU - Das, Amit AU - Chanda, Bhabatosh PY - 2007/02/01/ UR - http://dx.doi.org/10.1016/j.patrec.2006.04.005 ER -