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Optoelectronic Detecting System for Inner Walls of Pipes
作者姓名:BAIBaoxing  MAHong
作者单位:[1]ChangchunInstituteofOpticsandFineMechanics,Changchun,130022,CHN [2]ChangchunInstituteofOpticsandFineMech,Changchun,130022,CHN
摘    要:This paper is concerned with a high characteristic image processing and recognition system that is used for inspecting real-time blemishes,streaks and cracks on the inner walls of high accuracy pipes .As a regular detector,the BP neural network is used for extracting features of the image inspected and classifying these images,it takes fully advantage of the function of artificial neural network ,such as the information distributed memory, large scale self-adapting parallel processing ,high fault-tolerant ability and so forth.Besides , an improved BP algorithm is used in the system for training the network ,and making the learning procedure of the net converges to the minimum of overall situation at high rate.

关 键 词:光电子探测  抽运特性  图形识别  神经网络
收稿时间:1998/2/20

Optoelectronic Detecting System for Inner Walls of Pipes
BAIBaoxing MAHong.Optoelectronic Detecting System for Inner Walls of Pipes[J].Semiconductor Photonics and Technology,1998,4(2):104-108.
Authors:BAI Baoxing  MA Hong
Abstract:This paper is concerned with a high characteristic image processing and recognition system that is used for inspecting real-time blemishes, streaks and cracks on the inner walls of high accuracy pipes. As a regular detector, the BP neural network is used for extracting features of the image inspected and classifying these images, it takes fully advantage of the function of artificial neural network, such as the information distributed memory, large scale self-adapting parallel processing, high fault-tolerant ability and so forth. Besides, an improved BP algorithm is used in the system for training the network, and making the learning procedure of the net converges to the minimum of overall situation at high rate.
Keywords:Feature Extraction  Image Recognition  Neural Network  Optoelectronic Detection
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