Content based image retrieval is a important research area in the field of image processing used for searching and retrieving images from large database. It uses virtual content of images comprises of low level feature extraction such as color, texture, shape & spatial locations to represent images in the database. The system retrieves similar images images when an example image or sketch is presented as input to the system. This paper provides review of the approaches used for extracting low level features, various distance measures for retrieval, various datasets used in CBIR & performance measures. Creation of a content-based image retrieval system implies solving a number of difficult problems, including analysis of low-level image features and construction of feature vectors, multidimensional indexing, design of user interface, and data visualization. Quality of a retrieval system depends, first of all, on the feature vectors used, which describe image content. The paper presents a survey of common feature extraction and representation techniques and metrics of the corresponding feature spaces. Color, texture, and shape features are considered.

Content based image retrieval (CBIR), Image retrieval, and feature extraction

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