Department   Ritsumeikan Asia Pacific University  College of Sustainability and Tourism
   Position   Professor
Language English
Publication Date 2010/06
Type Research paper (Academic/Professional Journal)
Title Texture Analysis for Food Recognition
Contribution Type Joint Work
Journal IEICE Technical Reports on Pattern Recognition and Media Understanding
Volume, Issue, Page 110(97),pp.69-74
Author and coauthor K. N. Do, J. Ohya
Details 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.