A comparative analysis of various approaches used for feature extraction in content based image retrieval.

Image retrievalis a technique to retrieve images by utilizing the features of the image like color, shape and texture. Almost all of the current image retrieval or CBIR (content-based image retrieval) system allow for querying-by-image, a technique wherein animage (or a single feature of an image) is selected by the user as the query. The system extracts the features of the query image, searches for images with similar features in the database, and return relevant result in the form of image to the user in order of their similarity to query. Image retrieval is very useful in many areas like art collection, face finding, crime prevention, photograph archives etc. There are several techniques or algorithms that are used for feature extraction in content based image retrieval. This paper create a review of techniques or number of those methods that are used for feature extraction in content based image retrieval that are Color histogram, Color moments, Gabor filter, Wavelet Transform, Zernika Moment(ZM) ,Chain code etc.