A novel efficient technique for extracting valid feature information
- Authors
- Park, Sang-Sung; Shin, Young-Geun; Jang, Dong-Sik
- Issue Date
- 15-Mar-2010
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Image retrieval; Feature information; Genetic algorithm; Support vector machine
- Citation
- EXPERT SYSTEMS WITH APPLICATIONS, v.37, no.3, pp.2654 - 2660
- Indexed
- SCIE
SCOPUS
- Journal Title
- EXPERT SYSTEMS WITH APPLICATIONS
- Volume
- 37
- Number
- 3
- Start Page
- 2654
- End Page
- 2660
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/116800
- DOI
- 10.1016/j.eswa.2009.08.013
- ISSN
- 0957-4174
- Abstract
- In this study, we proposed a quick and accurate algorithm for content-based image classification. The proposed method is also used to retrieve similar images from databases. In this paper color and texture information are used to represent image features. The basic idea is to extract color information about global and local features of images. A global color feature is extracted by an RGB model. While, a local color feature is extracted by an HSV model. In the case of a local feature, if it cannot be classified, the result is inaccurate retrieval. A GA (genetic algorithm) is used to extract local features which can be classified. Local features extracted by a GA are optimal representative features. In the experiment, the accuracy of image classification is measured using the proposed algorithm. Also, we compared the previous algorithm with the proposed algorithm in terms of image classification performance. As a result, the proposed algorithm showed higher performance in terms of accuracy. (C) 2009 Elsevier Ltd. All rights reserved.
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- Appears in
Collections - Graduate School > Graduate School of management of technology > 1. Journal Articles
- College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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