K-Means Algorithm Using Texture Directionality for Natural Image Segmentation
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概要
- 論文の詳細を見る
The goal of this research is to describe relations between impressions and elements in an image (i.e. color, texture and contours). Adequate image segmentation technique to extract these elements is required. We think that a sketch and a realistic painting are examples of optimal segmented images for our purpose because brush strokes are seem to be segmented areas and realistic paintings should remain the same impression as the model. For the reason, in this paper the segmentation technique which can create realistic painting-like segmentation is exploited. It is shown that the realistic painting-like segmentation is suitable for analyzing images.
- 社団法人映像情報メディア学会の論文
- 1998-01-14
著者
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NAKAJIMA Masayuki
Graduate School of Information Science & Engineering, Tokyo Institute of Technology
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Nakajima Masayuki
Graduate School Of Information Science And Engineering Tokyo Institute Of Technology
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Kasao Atsushi
Graduate School of Information Science and Engineering, Tokyo Institute of Technology
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Kasao Atsushi
Graduate School Of Information Science And Engineering Tokyo Institute Of Technology
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Nakajima Masayuki
Graduate School Of Information And Engineering Tokyo Institute Of Technology
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