图像分割技术在去皮荸荠洁净度定量中的应用

Quoc-Nguyen Banh, Anh-Chuong Le, Quoc-Thang Dang, Anh-Son Tran, V. Dong
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引用次数: 0

摘要

在本研究中,为了对荸荠去皮质量进行评价,主要通过荸荠去皮机构对荸荠去皮机进行优化,该机构是安装在荸荠去皮机顶部的旋转刀具。确定了最佳切削参数条件,包括切削角度、切削高度、切削速度和剥离时间。本实验中具有代表性的质量参数是两个特征:清洁度值(CV)和剩余重量。关于CV的获取方法,第一阶段采用数码相机捕捉去皮荸荠的原始图像。然后利用图像处理技术将图像转换为8位灰度。在接下来的步骤中,利用图像分割方法提取图像的特征。同时,对菱角未剥皮和完整的外边界进行阈值分割。最后,利用未剥落的皮肤像素面积与完整的外边界面积之比得到CV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Image Segmentation Technique to Quantify Cleanliness Value of Peeled Water Chestnut
In this research paper, in order to gain assessment on the quality of peeled water chestnut, the optimization of the water chestnut peeling machine is primarily conducted via the peeling mechanism, which is the rotating cutter assembled on the top of the machine. The optimal cutting parameters' conditions, including cutting angle, cutting height, cutting velocity and peeling du-ration are determined. The quality parameters representative in this experiment are the two characteristics: Cleanliness Value (CV) and Remaining Weight. As regards the method of obtaining CV, in the first stage, raw image of peeled water chestnut is captured by digital camera. After that, the image is transformed to 8-bit Grey Scale by applying image processing technique. In the following step, image segmentation method is utilized in order to extract features of image. Meanwhile, the thresholding algorithm is applied for unpeeled skin and full outer boundary of water chestnut. Finally, the CV can be obtained by the ratio of pixel area of unpeeled skin to area of full outer boundary.
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