| 大口径精密表面疵病的数字化检测系统 |
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| 引用本文： | 范勇,陈念年,高玲玲,贾渊,王俊波,程晓锋.大口径精密表面疵病的数字化检测系统[J].强激光与粒子束,2009,21(7). |
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| 作者姓名： | 范勇 陈念年 高玲玲 贾渊 王俊波 程晓锋 |
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| 作者单位： | 1. 西南科技大学 计算机科学与技术学院, 四川 绵阳 621010;2. 西南科技大学 国防科技学院, 四川 绵阳 621010;3. 中国工程物理研究院 激光聚变研究中心, 四川 绵阳 621900 |
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| 基金项目： | 国家自然科学基金，四川省教育厅重点项目 |
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| 摘 要： | 根据散射光成像原理，采用大小两个视场来获取不同精度的暗背景下的亮疵病图像，设计了完整的数字化表面疵病检测系统。该系统采用多区域自适应阈值分割算法对图像进行分割，然后采用基于等价归并标记方法快速提取疵病的特征参数，最后利用BP神经网络对疵病进行分类。实验结果表明该方法既满足实时性需求，又取得了较好的分类检测效果。
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| 关 键 词： | 惯性约束聚变 疵病 快速标记算法 特征参数 分类准则 |
| 收稿时间： | 1900-01-01; |
Digital detection system of surface defects for large aperture optical elements |
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| Fan Yong,Chen Niannian,Gao Lingling,Jia Yuan,Wang Junbo,Cheng Xiaofeng.Digital detection system of surface defects for large aperture optical elements[J].High Power Laser and Particle Beams,2009,21(7). |
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| Authors: | Fan Yong Chen Niannian Gao Lingling Jia Yuan Wang Junbo Cheng Xiaofeng |
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| Affiliation: | 1. School of Computer Science and Technology, Southwest University of Science Technology, Mianyang 621010, China;2. School of Defense Technology, Southwest University of Science Technology, Mianyang 621010, China;3. Research Center of Laser Fusion, CAEP, P. O. Box 919-988, Mianyang 621900, China |
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| Abstract: | Based on the light defect images against the dark background in a scattering imaging system,a digital detection system of surface defects for large aperture optical elements has been presented.In the system,the image is segmented by a multi-area self-adaptive threshold segmentation method,then a pixel labeling method based on replacing arrays is adopted to extract defect features quickly,and at last the defects are classified through back-propagation neural networks.Experiment results show that the system can achieve real-time detection and classification. |
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| Keywords: | ICF defect fast labeling algorithm feature parameter classification rule |
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