Image Recognition of 85 Food Categories by Feature Fusion
Multimedia（2010）
摘要
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.
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关键词
food image,classification rate,prototype system,automatic food image recognition,color histogram,gradient histogram,feature fusion,food categories,gabor feature,image recognition,food category,multiple kernel learning,cellular-phone camera,histograms,feature extraction,learning artificial intelligence,image fusion,health care,image features,kernel,food technology,support vector machines
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