Food image classification using local appearance and global structural information

@article{Nguyen2014FoodIC,
  title={Food image classification using local appearance and global structural information},
  author={Duc Thanh Nguyen and Zhimin Zong and Philip Ogunbona and Yasmine C. Probst and Wanqing Li},
  journal={Neurocomputing},
  year={2014},
  volume={140},
  pages={242-251}
}
This paper proposes food image classification methods exploiting both local appearance and global structural information of food objects. The contribution of the paper is threefold. First, non-redundant local binary pattern (NRLBP) is used to describe the local appearance information of food objects. Second, the structural information of food objects is represented by the spatial relationship between interest points and encoded using a shape context descriptor formed from those interest points… CONTINUE READING
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