Feature Selection and Extraction for Content-Based Image Retrieval

  IJMTT-book-cover
 
International Journal of Mathematical Trends and Technology (IJMTT)          
 
© 2012 by IJMTT Journal
Volume-3 Issue-2                           
Year of Publication : 2012
Authors : E. Saravana Kumar , A. Sumathi, K. Latha

MLA

E. Saravana Kumar , A. Sumathi, K. Latha "Feature Selection and Extraction for Content-Based Image Retrieval"International Journal of Mathematical Trends and Technology (IJMTT),V3(2):70-73.June 2012. Published by Seventh Sense Research Group.

Abstract
Content-Based Image Retrieval is a technique that utilizes the visual content of an image to search for similar images in large scale image databases. The visual content of an image represents the low-level features extracted from the image. These primarily constitute color, shape and texture features. The precision of image classification and image retrieval is mainly based on image feature extraction. More distinguished image features will yield better results in classification and retrieval process. Thus feature selection and feature extraction are the important tasks to be considered in image retrieval process. This paper aims to discuss about feature selection and an efficient method for feature extraction is proposed for image retrieval process.

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Keywords
Content-Based Image Retrieval, Euclidean Distance Method, Relevance Feedback, Feature Vector