A self-learning machine vision system

被引:0
|
作者
Kelley, M [1 ]
机构
[1] JAI PULNiX Inc, Sunnyvale, CA 94089 USA
来源
INTELLIGENT MANUFACTURING | 2004年 / 5263卷
关键词
neural network; smart camera; ZISC; pattern recognition; ZiCAM; image processing; vision system;
D O I
10.1117/12.518547
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Reliable and productive manufacturing operations have depended on people to quickly detect and solve problems whenever they appear. Over the last 20 years, more and more manufacturing operations have embraced machine vision systems to increase productivity, reliability and cost-effectiveness, including reducing the number of human operators required. Because of these two key factors, increased technical complexity and an fewer resources, the people who continue to work in the factory are finding it ever more difficult to deal with issues that involve the production line's sophisticated machine vision equipment. An image processing technology is now available that enables a system to match an operator's subjectivity. A hardware-based implementation of a neural network system enables a vision system to "think" and "inspect" like a human, with the speed and reliability of a machine.
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页码:66 / 76
页数:11
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