Food log by analyzing food images
Food log by analyzing food images
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DOI：
10.1145/1459359.1459548
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发表时间：
2008-10
期刊：
影响因子：
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通讯作者：
Keigo Kitamura;T. Yamasaki;K. Aizawa
中科院分区：
文献类型：
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作者：
Keigo Kitamura;T. Yamasaki;K. Aizawa
本文介绍了一种食物记录系统，该系统能够将食物图像与其他图像区分开来，分析食物平衡，并将食物记录可视化。图像处理基于由颜色直方图、DCT系数、检测到的图像模式等组成的特征向量。利用支持向量机对食物图像进行检测，并对食物平衡进行分析。实验结果表明，食物图像提取的准确率在88%以上，食物平衡估计的准确率在73%以上。
In this paper, a food-logging system that can distinguish food images from other images, analyze the food balance, and visualize the log is presented. The image processing is based on feature vectors consisting of color histograms, DCT coefficients, detected image patterns and so forth. Support Vector Machine (SVM) was used to detect food images and to analyze the food balance. Experimental results show that the food image extraction presents above 88% of accuracy and the food balance estimation is achieved with more than 73% of accuracy.