Content Based Image Retrieval using Color, Texture and Shape features for fruit images
Pradeep R. Taware · 2014
In this paper Color, Texture and shape feature is used for retrieval of fruit images from database .The database contains a wide variety of fruit images. Moreover success of CBIR depends on the choice of the method used to generate feature vector, similarity measure and accuracy of segmentation technique employed. The accuracy of the system can be increased by retrieving images based on their color, texture and shape feature similarity. For color Mean, variance and standard deviation is computed. For texture co-occurrence based entropy, energy, correlation are calculated and for shape, using Seeded Region Growing algorithm and Canny edge detection the images are preprocessed and then Shape features such as extent, eccentricity, equivalence diameter, circularity and solidity is measured. Euclidean distance measure is used for retrieval of images. Experimental results have shown that the proposed system can improve the retrieval accuracy. The system is tested on 250 fruit images downloaded from internet.