针对目前自动光学检测系统在进行焊点检测时容易出现缺陷误报和漏报，以及智能化程度不高的问题，提出了一种基于神经网络的检测方法。
In order to overcome the error alarming and unintelligence of the automatic optical inspection(AOI) system for the solder joint inspection, a new inspecting method based on neural network is proposed.
根据苹果光学反射特性建立了一套适于苹果坏损自动检测的计算机图像系统。
On the optical reflectance properties of apples a computer image system for automatic detection of defects on apples is built.
为大型光学系统中光学元件损伤的在线、自动化检测提供了一种有用的技术途径。
The image processing method can provide a useful approach for online inspection and automatization inspection of damage in optics.
该系统具有测量速度快、检测精度高、实时性强及数据处理自动化等特点，它是近代光学、光电技术与微机技术的有机结合。
The measuring system, possessing advantages of high precision and real time measurement, by using modern optics, opto-electronic technique and microcomputer is also described.
基于强激光系统光学元件损伤的在线暗场成像检测，提出了一种无损、自动、快速检测的新算法。
A new algorithm of nondestructive, automatic and high-speed inspection is proposed for dark-field image to be used to inspect online optic component damage on high power laser system.
该系统具有测量速度快、检测精度高及数据处理自动化等特点。整个系统是近代光学、光电技术与微机技术的有机结合。
It possesses the advantages of high precision and high efficiency, for it is a combination of modern optics, photoelectric technique and microcomputer.
大口径光学组件面形检测系统中，激光光斑的分割、质心提取和背表面光斑的自动剔除算法关系到系统的检测精度。
In the large optical components topography measurement system, the accuracy of measurement is greatly related to laser spot segmentation, centroid extraction and back surface spot removal.
大口径光学组件面形检测系统中，激光光斑的分割、质心提取和背表面光斑的自动剔除算法关系到系统的检测精度。
In the large optical components topography measurement system, the accuracy of measurement is greatly related to laser spot segmentation, centroid extraction and back surface spot removal.
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