摘要
苹果质量备受人们的关注,如何精准高效地对苹果质量进行检测分级是目前这一领域研究的重要内容。基于Matlab软件设计自动化程序,采集图像进行图像处理。通过视觉检测平台采集图片、对图片预处理、将处理后的图像进行大小、颜色、缺陷3方面检测,分别得到每项检测后的等级A、B、C,汇总单项等级得到整个苹果质量等级。出于自动识别及分级的目的,运用深度学习的方法,对获取到的图像进行特征提取,训练分类器,最终实现对苹果总体质量的评级,并以图像检测结果作为标准测试其准确率。综合上述分析提出一种基于深度学习的苹果质量检测及分级方法,该方法可准确快速地对苹果进行分级,能很好地完成实验目的,同时也体现出深度学习在图像处理方面的快速发展与重要性,并为其在其他领域的应用提供思路。
The quality of apples has attracted much attention.How to accurately and efficiently test and grade the quality of apples is also an important part of the current research in this field.An automated program was designed based on Matlab software to collect images for image processing.Collect pictures through the visual inspection platform,preprocess the pictures,and test the processed images for size,color and defects,and obtain the grades A,B and C after each inspection,and summarize the individual grades to obtain the entire apple quality grade.For the purpose of automatic identification and grading,the method of deep learning is used to extract the features of the obtained images,train the classifier,and finally achieve the overall quality rating of apple,and use the image detection results as the standard to test its accuracy.Based on the above analysis,an apple quality detection and classification method based on deep learning is proposed,which can accurately and quickly classify apples,and can well accomplish the purpose of the experiment.which shows the rapid development and importance of deep learning in image processing,and provides ideas for its application in other fields.
作者
项辉宇
黄恩浩
冷崇杰
张勇
XIANG Huiyu;HUANG Enhao;LENG Chongjie;ZHANG Yong(Artificial Intelligence Academy,Beijing Technology and Business University,Beijing 100048,China)
出处
《食品安全导刊》
2022年第22期48-53,共6页
China Food Safety Magazine
