Presentation 2010-06-25
Texture Analysis for Food Recognition
Khanh N.DO, Jun OHYA, Davar PISHVA,
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Abstract(in English) 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.
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Keyword(in English) Food image processing / texture analysis / gray level co-occurrence matrix / Fourier transforms
Paper # PRMU2010-50,HIP2010-39
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Conference Information
Committee PRMU
Conference Date 2010/6/17(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Texture Analysis for Food Recognition
Sub Title (in English)
Keyword(1) Food image processing
Keyword(2) texture analysis
Keyword(3) gray level co-occurrence matrix
Keyword(4) Fourier transforms
1st Author's Name Khanh N.DO
1st Author's Affiliation Graduate school of Global Information and Telecommunication Studies, Waseda University()
2nd Author's Name Jun OHYA
2nd Author's Affiliation Graduate school of Global Information and Telecommunication Studies, Waseda University
3rd Author's Name Davar PISHVA
3rd Author's Affiliation Institute of Information and Communication Technology, Ritsumeikan Asian Pacific University
Date 2010-06-25
Paper # PRMU2010-50,HIP2010-39
Volume (vol) vol.110
Number (no) 97
Page pp.pp.-
#Pages 6
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