ABSTRACT
In the diversified development of glass industry and technology products, the demand of quality performance of the glass surface increases. The surface quality detection is becoming more and more strict, especially the evaluation of the surface quality defects. The glass surface quality detection means, and ability has certain limitations, most methods for artificial detection, improve the detection accuracy and objectivity. The authors studied the glass surface quality of machine vision detection method based on the detailed discussion of computer vision and image processing technology. This study draws the conclusion that machine vision plays an important role in the quality detection of the glass surface and its high efficiency & accuracy has broad application prospects.
Acknowledgments
The authors would like to acknowledge Project (Political 201709), supported by The 2017 horizontal subject of Dongguan Polytechnic, Dongguan, the development and design of the industrial visual inspection system for the surface quality of glass products.
Disclosure statement
No potential conflict of interest was reported by the authors.