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Foreign Material Detection for Scallion Processing Industry Using HSV Color Space

Wu-Sung Yao, Chun-Yi Lin

Abstract


In this paper, an optical foreign substance detection system is designed to address the problem of foreign substances mixed in food. The five color spaces of RGB, HSV, YCrCb, CIELab, and CIELuv are compared by using scallion images and non-scallion images to seek the color space that is the most suitable for the scallion processing. The designed image algorithms are given to filter out food raw materials and background images. The images on the conveyor belt are captured by stacking backlight sensors. The technology of image filtering is based on HSV color space to determine the production line and whether there is a foreign substance or not. The purpose of this study is to help traditional human detection, reduce the omissions in inspections caused by fatigue, laziness, and other problems, and at the same time save labor costs, and increase production speed, which can help the food production lines reduce the problem of mixed foreign objects in food raw materials.


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