Color Histogram based Image Retrieval – A Survey

Abstract

Content Based Image Retrieval (CBIR) is an active research area in the field of digital image processing. In Content Based Image Retrieval, images would be described by their visual content comprising of low level feature extraction such as color, texture, shape, edge and size. Representation of visual features and similarity match are important issues in CBIR. Color feature is one of the most widely used low level features. Compared with shape feature and texture feature, color feature shows better stability and is more insensitive to the rotation and zoom of image. Color not only adds beauty to objects but also records more information in particular color histogram for retrieve. Hence it can be used as powerful tool in content-based image retrieval. This paper provides a brief survey of CBIR using color feature in particular as it is the effective feature to express visual information, which is invariant on complexity. The different methods adopted to compare similarity of images have been briefed in addition to the discussion of commonly used color models and performance measures for CBIR.

Keywords: CBIR, Color Models, Color Features, Similarity Measures, Performance Measure.