Umesh K K¹ and Suresha², ¹Sri Jayachamarajendra College of Engineering, India and ²University of Mysore, India

Image retrieval system is an active area to propose a new approach to retrieve images from the large image database. In this concerned, we proposed an algorithm to represent images using divisive based and partitioned based clustering approaches. The HSV color component and Haar wavelet transform is used to extract image features. These features are taken to segment an image to obtain objects. For segmenting an image, we used modified k-means clustering algorithm to group similar pixel together into K groups with cluster centers. To modify K-means, we proposed a divisive based clustering algorithm to determine the number of cluster and get back with number of cluster to k-means to obtain significant object groups. In addition, we also discussed the similarity distance measure using threshold value and object uniqueness to quantify the results.

Feature Extraction, Pixel Segmentation, Modified k-means Clustering, Similarity Distance Measure, Object Clustering, Object Uniqueness.