光电工程, 2013, 40 (11): 22, 网络出版: 2013-12-04  

基于两级图像采集的镜片疵病在线检测方法

On-line Defect Detection Method Based on Two Image Acquisition Structures
作者单位
江苏大学机械工程学院, 江苏 镇江 212013
摘要
根据树脂镜片在线检测的要求和特点, 提出一种基于机器视觉的在线疵病检测方法。针对不同尺寸的疵病, 设计了基于两级图像采集的在线检测系统, 完成对镜片疵病的检测。利用第一级图像采集系统检测部分疵病, 获得点杂质和气泡等疵病的详细特征, 同时可以获取划痕和羽毛的长度、位置和数量等信息和包含划痕或羽毛的敏感区域的位置, 并发送信号控制第二图像采集系统的工作。利用第二图像采集系统的传送带和一维导轨的移动对敏感区域定位, 检测划痕和羽毛的直径。本文设计的方法解决了系统成本高、检测速度慢、数据量大等技术问题, 满足在线检测的需要。实验表明:系统检测速度为每片 1.5 s; 与子孔径拼接技术相比, 数据量最少减少约 88%, 最多减少约 96%。
Abstract
According to the requirements and characteristics of the hard resin lens on-line detection, an on-line defect detection method based on machine vision is proposed. An on-line detection system with two image acquisition structures is designed to detect all of the defects with different sizes. The first image acquisition system is used to detect the characteristics of the defects such as the point-like impurities and bubbles, and to obtain the information, including the length, amount and location of the scratches, and the location of sensitive areas contain the scratches and feathery impurities, and to control the working status of the second image acquisition system. The second image acquisition system is used to detect the diameter of the scratches and feathery impurities, after locating the position of sensitive areas with the movement of the conveyor belt and the one-dimensional linear guiding of the second image acquisition structure. This proposed method is able to solve the technical problems such as high cost, low-detection-speed and mass-data, which meets the needs of online detection. Experiments show that detecting speed of the system is 1.5 s / piece. Compared with subaperture stitching, the least amount of data is reduced by about 88% and a decrease of approximately 96% at most.

姚红兵, 曾祥波, 马桂殿, 郑学良, 李亚茹, 高原, 于文龙, 顾寄南, 蒋光平. 基于两级图像采集的镜片疵病在线检测方法[J]. 光电工程, 2013, 40(11): 22. YAO Hongbing, ZENG Xiangbo, MA Guidian, ZHENG Xueliang, LI Yaru, GAO Yuan, YU Wenlong, GU Jinan, JIANG Guangping. On-line Defect Detection Method Based on Two Image Acquisition Structures[J]. Opto-Electronic Engineering, 2013, 40(11): 22.

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