人工智能
灰度
分割
计算机科学
模式识别(心理学)
分类器(UML)
瘀伤
计算机视觉
图像分割
特征提取
移动电话
像素
材料科学
医学
电信
外科
作者
Changshu Wang,Changsheng Li,Yanjiang Huang,Xianmin Zhang
摘要
Complex manufacturing makes the screens one or more defects simultaneously. Effective detection of defects is crucial in the manufacturing processes of mobile phone glass screens. In this paper, we concentrate on extracting and classifying some typical defects, such as scratch, bruise, pit and blister. Firstly, we use morphological filter to smooth background noise, and an improved gamma grayscale transformation is proposed to enhance the contrast. Then, a double threshold segmentation algorithm, based on area threshold and gray threshold, is presented to extract defects from background. Finally, according to different optimal segmentation feature values of different defects, a binary tree classifier is constructed to classify defects. The experiment results show that the proposed method can extract and recognize typical defects precisely.
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