Application of the intelligent system of image processing to inspection of steel bridges coating

• Main Authors: Gwo-Zery Preng, 彭國瑞
• Other Authors: Shyh-Chang Huang
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/03734339122937345164

碩士 === 國立交通大學 === 土木工程系 === 89 === Intelligent computerized system can simulate human expertise as well as analyze and process vast amounts of data instantaneously. This report presents a hybrid intelligent computerized system for bridge surface quality assessment. This system can be assessed to identify and measure the steel bridge coating condition and defects through computers to analyze image of the areas. Moreover, neural network are used to train the system to automate the image processing and replicate the experts’ knowledge in identifying the defects. The major difference between the proposed system and the existing commercial image processors is that the model has the intelligent ability to self-learn through neural networks and makes the decision of accepting or rejecting the assessed quality with pre-known risks. Finally those cases are successful to apply image processing and neural network techniques for bridges surface quality assessment to make the process objective, quantitative, consistent, and reliable