1Dept of Information Technology, Sathyabama University, Old Mahapalipuram Road, Chennai, Tamil Nadu, Pin-600119.
2Dept of Electronics and communication Engg., Anna University, Chennai.
In a content based image retrieval system, target images are sorted by feature similarities with respect to the query (CBIR)[5].In this paper, we propose to use K-means clustering for the classification of feature set obtained from the histogram. Histogram provides a set of features for proposed for Content Based Image Retrieval (CBIR). Hence histogram method further refines the histogram by splitting the pixels in a given bucket into several classes[1]. Here we compute the similarity for 8 bins and similarity for 16 bins. Standard histograms, because of their efficiency and insensitivity to small changes, are widely used for content based image retrieval. But the main disadvantage of histograms is that many images of different appearances can have similar histograms because histograms provide coarse characterization of an image.
