Content Based Image Retrieval Using Hierachical and Fuzzy C-Means Clustering
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2017 by IJCTT Journal|
|Year of Publication : 2017|
|Authors : Prof.S.Govindaraju, Dr.G.P.Ramesh Kumar|
|DOI : 10.14445/22312803/IJCTT-V44P115|
Prof.S.Govindaraju, Dr.G.P.Ramesh Kumar; "Content Based Image Retrieval Using Hierachical and Fuzzy C-Means Clustering". International Journal of Computer Trends and Technology (IJCTT) V44(2):89-95, February 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Grouping images into semantically meaningful categories using low-level visual feature is a challenging and important problem in content based image retrieval. CBIR is a part of image processing. We know that with the development of the internet and the availability of image capturing devices such as digital cameras, image scanners, and size of the digital image collection is increasingly rapidly and hence there is a huge demand for effective image retrieval system. Normally CBIR is retrieving/ searching stored images from a collection by comparing features automatically extracted from the image themselves. The most common features used are mathematical measure is texture, color and shape. Clustered images are utilized by content-based image retrieval and querying system that requires effective query matching in large image database. Particularly, Inthis paper we are using HFCM Algorithm. It has the combinational advantage of both fuzzy and possiblistic approaches. The experimental results suggest that the proposed image retrieval technique results in better retrieval.
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Query, Hybrid Fuzzy C-Means, Content Based Image Retrieval.