智慧型影像處理於鋼構橋樑表面塗裝檢測之應用

Abstract

近年來，由於電腦技術的發展讓影像處理技術具有實用性，而不需花費昂貴成本，也因為電腦處理器運算能力的不斷提昇，讓我們可以利用影像處理裝置與相關影像處理技術與軟體，將複雜的影像加以分析。而本研究在探討一種智慧型判斷模式，其結合影像處理與類神經網路，對於鋼構橋樑表面塗裝鏽蝕狀況進行辨認與量測，在系統中利用一些案例來訓練類神經網路，使其具有人類的經驗，故此系統與現行商業影像處理系統的主要差異在於其運用類神經網路，具有自我學習能力，並且具有容錯性。在本文中首先對於鋼構橋樑塗裝系統與鏽蝕機制加以介紹，並對於研究中相關運用之影像處理技術與方法予以說明，再者探討類神經網路各個網路架構與演算法，在研究中利用案例學習以建構網路架構並進行案例測試，最後就測試結果加以探討。

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