使用图像识别分析食物摄入的卡路里

Natta Tammachat, N. Pantuwong
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引用次数: 20

摘要

近年来,健康是人们关注的话题。很明显,吃高热量的食物会给我们的健康带来一些问题。记录每餐食物摄入的卡路里量是解决这一问题的可行方法之一。虽然人们可以记录他们的饮食并与医生或专家讨论,但这不是那么方便,他们无法知道饭前的卡路里量。本文提出了一种图像处理技术,用于识别用户拍摄的食物图像。从输入的食物图像中,用户可以通过使用所提出的算法了解他们每餐将摄入的卡路里量。该方法利用纹理和颜色的多个特征创建特征向量,然后利用支持向量机对食物图像进行分类。在这项研究中,我们关注的是泰国菜。为了训练支持向量机,我们根据食物类型和卡路里量对示例食物图像进行分组。我们对两组样本食物进行了实验,以评估所提出算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calories analysis of food intake using image recognition
In recent year, healthy is a topic that people concern. It is obviously that eating the food with high amount of calories cause several problems to our health. Recording the amount of calories of the food intake in each meal is one of the stretchy to solve such problem. Although the people can record their meal and discuss with doctors or experts, it is not so convenient and they cannot know the amount of calories before the meal. This paper presents a technique of image processing to recognize images of food taken by users. From the input food images, the users can understand the amount of calories they will take in each meal by using the proposed algorithm. Our method creates feature vector using several features about texture and color, then classify the food images using SVM. In this study, we focused on Thai food. To train the SVM, we group the example food images by food type and the amount of calories. We conduct the experiment to evaluate the performance of the proposed algorithm for both groups of example food.
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