DOIONLINE

DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-594

Publish In
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN
Journal Home
Volume Issue
Issue
Volume-2,Issue-4  ( Apr, 2014 )
Paper Title
SOM And SVM Based Feature Extraction And Detection Of Objects In Images
Author Name
Preeti Ahirwar, Samant Verma, Yogendra Kumar Jain
Affilition
Research Scholar, Assistant Professor, Head of Department, Department of Computer Science and Engineering, Samrat Ashok Technological Institute, Vidisha (M.P.) India
Pages
29-34
Abstract
Abstract— Image retrieval is a technique in which the image is retrieved using feature extraction or tagging so that it can be used for a variety of applications. Although there are various techniques implemented for the image retrieval such as using Fuzzy Classifier, the methodology used for the image retrieval using Fuzzy is efficient but has more error rate and image retrieval rate is low. Hence, an efficient technique is proposed here for the image retrieval using SOM based clustering, so that the clustering of the specified objects in the image is done and image is retrieved by training those features of the image. The methodology adopted here provides more retrieval rate as compared to the previous technique of image retrieval. The idea is to convert the image into HSV color space providing multi-resolution structure and applying SOM clustering to cluster and detect the features of the image, now segment only the features, which contains object in the image.
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