Presentation 2009/1/5
AUTOMATIC SELECTION AND ADJUSTMENT OF FEATURES FOR IMAGE CLASSIFICATION(International Workshop on Advanced Image Technology 2009)
Kenji Saiki, Tomoharu Nagao,
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Abstract(in English) Recently, image classification has been an important task in various fields. Generally, the performance of image classification is not good without the adjustment of image features. Therefore, it is desired that the way of automatic feature extraction. In this paper, we propose an image classification method which adjusts image features automatically. We assume that texture features are useful in image classification tasks because natural images are composed of several types of texture. Thus, the classification accuracy rate is improved by using distribution of texture features. We obtain texture features by calculating image features from a current considering pixel and its neighborhood pixels. And we calculate image features from distribution of textures feature. Those image features are adjusted to image classification tasks using Genetic Algorithm. We apply proposed method to classifying images into "head" or "non-head" and "male" or "female".
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Keyword(in English) image classification / feature extraction / Genetic Algorithm / Support Vector Machine
Paper # IE2008-134
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Committee IE
Conference Date 2009/1/5(1days)
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Registration To Image Engineering (IE)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) AUTOMATIC SELECTION AND ADJUSTMENT OF FEATURES FOR IMAGE CLASSIFICATION(International Workshop on Advanced Image Technology 2009)
Sub Title (in English)
Keyword(1) image classification
Keyword(2) feature extraction
Keyword(3) Genetic Algorithm
Keyword(4) Support Vector Machine
1st Author's Name Kenji Saiki
1st Author's Affiliation Graduate School of Environment and Information Sciences Yokohama National University()
2nd Author's Name Tomoharu Nagao
2nd Author's Affiliation Graduate School of Environment and Information Sciences Yokohama National University
Date 2009/1/5
Paper # IE2008-134
Volume (vol) vol.108
Number (no) 373
Page pp.pp.-
#Pages 4
Date of Issue