Fast-axis collimating lens recognition algorithm based on machine vision. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Wu, Guodong; Zhu, Ma; Jiang, Qiuyue; Sun, Xiang
• Is Part Of: Journal of physics. Volume 1820:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1820/1/012157
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to solve the problem of low efficiency and low accuracy of manually picked fast shaft collimation lens in actual production, the method of recognition of fast shaft collimation lens based on machine vision is studied. Using industrial camera to achieve image acquisition, using HALCON software to pre-process the image of fast-axis collimated lens, edge detection and other aspects of research, through the platform verification, the results show that the processed image is clear and easy to identify. In the lens placement is not accurate, the background is dirty can still ensure a better positioning effect, This study has some reference significance for visual recognition in the actual production of fast-axis collimation lens.