Feature Selection and Extraction for Content-Based Image Retrieval

E. Saravana Kumar; A. Sumathi; K. Latha

doi:https://doi.org/10.14445/22315373/IJMTT-V3I2P506

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 3 | Issue 2 | Year 2012 | Article Id. IJMTT-V3I2P506 | DOI : https://doi.org/10.14445/22315373/IJMTT-V3I2P506

Feature Selection and Extraction for Content-Based Image Retrieval

E. Saravana Kumar , A. Sumathi, K. Latha

Citation :

E. Saravana Kumar , A. Sumathi, K. Latha, "Feature Selection and Extraction for Content-Based Image Retrieval," International Journal of Mathematics Trends and Technology (IJMTT), vol. 3, no. 2, pp. 70-73, 2012. Crossref, https://doi.org/10.14445/22315373/IJMTT-V3I2P506

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.

Keywords

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

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