Texture Analysis for Food Recognition

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概要

• 論文の詳細を見る

• This paper studies the effectiveness of texture analysis methods for classifying different food items having the same color. This paper studies two texture analysis methods: gray-level co-occurrence matrix (GLCM) based features and Fourier Transform (FT) based features. We carried out experiments on testing the effectiveness of the two texture features using six different food items, where two food items having three colors: white, red and yellow are used. From the experimental results, it turns out that GLCM features and FT's spatial frequency based features are promising.

• 2010-06-17

著者

• OHYA Jun

  Graduate School of Global Information and Telecommunication and Studies, Waseda University

• N.DO Khanh

  Graduate school of Global Information and Telecommunication Studies, Waseda University

• PISHVA Davar

  Institute of Information and Communication Technology, Ritsumeikan Asian Pacific University

• Pishva Davar

  Institute Of Information And Communication Technology Ritsumeikan Asian Pacific University

• N.do Khanh

  Graduate School Of Global Information And Telecommunication Studies Waseda University

• Ohya Jun

  Waseda Univ. Tokyo Jpn

• Do Khanh

  Graduate School Of Global Information And Telecommunication Studies Waseda University

• Ohya Jun

  Graduate School Of Global Information And Telecommunication And Studies Waseda University

• Ohya Jun

  Graduate School of Global Information and Telecommunication Studies, Waseda University

• Ohya Jun

  Graduate School of Global Information and Telecommmication StudiesWaseda Unlversity

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