FOOD IMAGE ANALYSIS: SEGMENTATION, IDENTIFICATION AND WEIGHT ESTIMATION

被引：0

作者：

He, Ye ^{[1
]}

Xu, Chang ^{[1
]}

Khanna, Nitin ^{[2
]}

Boushey, Carol J. ^{[3
]}

Delp, Edward J. ^{[1
]}

机构：

[1] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA

[2] Graphic Era Univ, Dept Elect Commun Engn, Dehra Dun, India

[3] Univ Hawaii Cancer Ctr, Cancer Epidemiol Program, Honolulu, HI USA

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME 2013) | 2013年

基金：

美国国家卫生研究院;

关键词：

Dietary Assessment; Image Segmentation; Object Identification; Weight Estimation;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes.

引用

页数：6

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