Title :
Image Recognition of 85 Food Categories by Feature Fusion
Author :
Hoashi, Hajime ; Joutou, Taichi ; Yanai, Keiji
Author_Institution :
Dept. of Comput. Sci., Univ. of Electro-Commun., Chofu, Japan
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.
Keywords :
feature extraction; food technology; image fusion; image recognition; learning (artificial intelligence); Gabor feature; automatic food image recognition system; bag-of-features; cellular phone camera; color histogram; feature fusion; food categories; gradient histogram; image fusion; multiple kernel learning; prototype system; feature fusion; food image recognition; multiple kernel learning;
Conference_Titel :
Multimedia (ISM), 2010 IEEE International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-8672-4
Electronic_ISBN :
978-0-7695-4217-1
DOI :
10.1109/ISM.2010.51
