Comparison of Color and Color with Edge Feature Extraction Using Contribution-Based Clustering Algorithm

Search and retrieval of images based on content has attracted considerable attention in recent years from the research community. Classification and Clustering algorithm are used to improve the result of Content based Image retrieval. This paper relies on a combination of color and edge features of image for the accurate retrieval of images. Color features are extracted by RGB color histogram and edge features are extracted by using canny edge detection algorithm. Contribution based Clustering algorithm is applied to those features to form the cluster of images. Experimental results have been tested on the test dataset of about 771 images from the Washington University database. Combination of Color with Edge features gives the better result than the standalone color extraction with contribution based clustering algorithm. Our experiment improves the recall value and f-measure value of image retrieval.