Image Recognition of 85 Food Categories by Feature Fusion

Authors:
Hajime Hoashi;Taichi Joutou;Keiji Yanai
Affiliations:
-;-;-
Venue:
ISM '10 Proceedings of the 2010 IEEE International Symposium on Multimedia
Year:
2010

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Abstract

Recognition of food images is challenging due to their diversity and practical for health care on foods for people. In this paper, we propose an automatic food image recognition system for 85 food categories by fusing various kinds of image features including bag-of-features~(BoF), color histogram, Gabor features and gradient histogram with Multiple Kernel Learning~(MKL). In addition, we implemented a prototype system to recognize food images taken by cellular-phone cameras. In the experiment, we have achieved the 62.52% classification rate for 85 food categories.