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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.