Recipe Recommendation Method by Similarity Measure with Food Image Recognition

Shota Tamaru, Hyuga Taki, Rune Usuki, T. Nakanishi
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Abstract

This paper presents a recipe recommendation method by similarity measure with food image recognition. In general, it is difficult for users with little cooking experience to find out what kind of dishes they can make from the ingredients they currently have. Therefore, we propose a system that recommends recipes based on the ingredients in the user's current inventory, thereby increasing the number of dishes in the user's cooking repertoire. This system uses camera images of foodstuffs as input, recognizes the foodstuffs, and searches for recipes. In the experiment, we conducted a questionnaire survey of the recognized food ingredients and a questionnaire survey of recipe suggestions, and the results showed that more than 3/4 of the respondents answered that the recognition results and recipe contents were correct for some of the images. In this way, possible for users to search for recipes with fewer steps.
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基于食物图像识别的相似度度量的食谱推荐方法
提出了一种基于食品图像识别的相似度度量的食谱推荐方法。一般来说,对于没有烹饪经验的用户来说,很难知道用现有的食材可以做出什么样的菜。因此,我们提出了一个系统,根据用户当前库存中的食材推荐食谱,从而增加用户烹饪曲目中的菜肴数量。该系统使用食物的相机图像作为输入,识别食物,并搜索食谱。在实验中,我们对识别的食品成分进行了问卷调查,并对食谱建议进行了问卷调查,结果显示,超过3/4的受访者回答识别结果和食谱内容对部分图像是正确的。这样,用户可以用更少的步骤搜索食谱。
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