AUTOMATIC SELECTION AND ADJUSTMENT OF FEATURES FOR IMAGE CLASSIFICATION

  • Saiki, Kenji (Graduate School of Environment and Information Sciences Yokohama National University) ;
  • Nagao, Tomoharu (Graduate School of Environment and Information Sciences Yokohama National University)
  • 발행 : 2009.01.12

초록

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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