Content Based Image Retrieval Using Color and Textural Features

Abstract: In this paper, a novel approach for content based image retrieval using color and textural features is presented. The system is developed and tested on 400 images in 5 different categories such as forest, water contained area, animals, cartoon and construction buildings images. The features extraction developed consists of the combination of textural and color features. The texture features are extracted through wavelet transformation and the color features with color histogram. The extraction of color features from digital images depends on an understanding of the theory of color and the representation of color in digital images. Color spaces are an important component for relating color to its representation in digital form. The transformations between different color spaces and the quantization of color information are primary determinants of a given feature extraction method. The approach is found to be robust in terms of accuracy and is 92.4% amongst five categories.

Keywords: content based image retrieval, color histogram, wavelet transform, texture