Cooking Ingredient Recognition Based on the Load on a Chopping Board during Cutting

2011 IEEE International Symposium on Multimedia Pub Date : 2011-12-01 DOI:10.1109/ISM.2011.69

Yoko Yamakata, Yoshiki Tsuchimoto, Atsushi Hashimoto, Takuya Funatomi, Mayumi Ueda, M. Minoh

引用次数: 10

Abstract

This paper presents a method for recognizing recipe ingredients based on the load on a chopping board when ingredients are cut. The load is measured by four sensors attached to the board. Each chop is detected by indentifying a sharp falling edge in the load data. The load features, including the maximum value, duration, impulse, peak position, and kurtosis, are extracted and used for ingredient recognition. Experimental results showed a precision of 98.1% in chop detection and 67.4% in ingredient recognition with a support vector machine (SVM) classifier for 16 common ingredients.

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基于切菜板负荷的烹饪配料识别

本文提出了一种基于切菜板上的载荷来识别菜谱配料的方法。负载由连接在电路板上的四个传感器测量。通过识别负载数据中的急剧下降沿来检测每个斩波。提取负载特征，包括最大值、持续时间、脉冲、峰位置和峰度，并用于成分识别。实验结果表明，支持向量机(SVM)分类器对16种常见成分的切痕检测准确率为98.1%，成分识别准确率为67.4%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2011 IEEE International Symposium on Multimedia

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