摘要
为了实现苹果分级完全自动化,研究了苹果表面缺陷图像分类方法。提取了苹果表面缺陷图像区域的特征参数。根据表面缺陷特征,同时考虑缺陷形状的投影畸变,提出了一种苹果表面缺陷分类方法。分类方法利用二叉树将一个复杂的多模式分类问题分解为多级的、相对简单的二类模式分类问题,并采用人工神经网络与阈值判别相结合的方法,将苹果表面缺陷分为碰压伤、刺伤、裂果、病虫果和虫伤。试验表明:该分类方法能将苹果表面缺陷进行分类。
To realize apple automatic grading completely, the method for classifying apple surface defect by digital image processing was researched. The feature parameters of blemish image region were extracted. According to features of apple surface defect and considering projective distortion of defect shape, a method for classifying apple surface defect was presented. The method divides a multi-pattern classification into the multilevel and simple two-pattern classification by binary tree. The method classifies defect into bruising, skin puncture, crack, maggoty fruit and insect bites by combining the neural networks with threshold judgement. Test shows that the method can be used to classify apple surface defect effectively.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2004年第6期138-140,共3页
Transactions of the Chinese Society of Agricultural Engineering
关键词
苹果
缺陷
分类
数字图像处理
apple
defect
classification
digital image processing
