用数字图像处理算法对葱的质量分级和大小进行分类

Bhai Nhuraisha I. Deplomo, J. D. dela Cruz, Jessie R. Balbin
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引用次数: 1

摘要

本研究介绍了一个基于菲律宾国家标准(PNS)的洋葱大小、颜色和纹理分类系统,该系统使用高斯模糊、Canny边缘、侵蚀、膨胀、轮廓、颜色掩蔽、像素每公制比、RGB和Blob等图像处理方法。Blob算法可以根据洋葱的等级来检测洋葱的纹理;A级(1级)、B级(2级)、C级(1级和2级的结合)和不合格。研究人员对球茎洋葱进行了一系列的实验测试,比较了人工分级和自动分级的质量分级。本研究采用的统计方法是t检验来比较人工分拣和自动分拣。根据地方标准,红洋葱的t值为0.1284,黄洋葱的t值为0.0178。结果小于临界值2.01。这意味着零假设被接受。总的来说,该系统可以通过图像算法确定洋葱鳞茎的大小、颜色和纹理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classifying Quality Grading and Size of Allium Cepa Using Digital Image Processing Algorithms
This study introduced the system that can classify the size, color, and texture of the onion based on Philippine National Standard (PNS) using image processing methods such as Gaussian Blur, Canny Edge, Erosion, Dilation, Contouring, Color Masking, Pixel per metric ratio, RGB, and Blob. The Blob algorithm can detect the texture of the onion according to its grade; Grade A(Grade 1), Grade B (Grade 2), Grade C (Combination of Grade 1 and Grade 2), and Reject. The researcher conducted series of experimental testing to compare the quality grading using manual and automatic classification of bulb onion. The statistical method used for this study is T-test to compare the manual sorting and automated sorting. The t-values for red onion based on local standards is 0.1284, while the yellow onion is 0.0178. The results are less than the critical value of 2.01. It means that the null hypothesis is accepted. Over all, the system can determine the size, color, and texture bulbs of onion using image algorithms.
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