IMAGE RETRIEVAL BASED ON FEATURE SELECTION METHOD

Abstract

Content-Based Image Retrieval (CBIR) look at retrieval of analogous images from a large database for a given input query image. It has outstretched applications in image processing and pattern recognition. In this paper texture feature is extracted from image using Gray Level Co-occurrence Matrix (GLCM) technique. The technique is used for calculation of statistical measures such as energy, correlation, homogeneity and contrast features. A feature selection technique is brought to select optimal features. Feature selection method based on the Genetic algorithm approach is adapted to improve the accuracy of content- based image retrieval systems. Feature selection iron out the curse of dimensionality reduction. The major advantage of this approach is that little human intrusion is required for retrieving the required images from the database. The method is evaluated on Coral Database. Performance analysis is done by using precision and recall.