Image Recognition of 85 Food Categories by Feature Fusion

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,...

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Bibliographic Details
Published in2010 IEEE International Symposium on Multimedia pp. 296 - 301
Main Authors Hoashi, H, Joutou, T, Yanai, K
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2010
Subjects
Feature extraction
feature fusion
food image recognition
Histograms
Image color analysis
Image recognition
Kernel
multiple kernel learning
Support vector machines
Training
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Summary: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.
ISBN:1424486726
9781424486724
DOI:10.1109/ISM.2010.51