Cellular neural networks for welding arc thermograms segmentation

作     者：Jamrozik, Wojciech 

作者机构：Silesian Tech Univ Inst Fundamentals Machinery Design PL-44100 Gliwice Poland 

出 版 物：《INFRARED PHYSICS & TECHNOLOGY》 (红外物理学与技术)

年 卷 期：2014年第66卷

页      面：18-28页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 0804[工学-仪器科学与技术] 0803[工学-光学工程] 0702[理学-物理学] 

主　　题：Thermovision Image segmentation Cellular neural networks Welding 

摘      要：Machine vision systems are used in many areas for monitoring of technological processes. Among this processes welding takes important place, where often infrared cameras are used. Besides reliable hardware, successful application of vision systems requires suitable software based on proper algorithms. One of most important group of image processing algorithms is connected to image segmentation. Obtainment of exact boundary of an object that changes shape in time, such as the welding arc, represented on a thermogram is not a trivial task. In the paper a segmentation method using supervised approach based on a cellular neural networks is presented. Simulated annealing and genetic algorithm were used for training of the network (template optimization). Comparison of proposed method to a well elaborated segmentation method based on region growing approach was made. Obtained results prove that the cellular neural network can be a valuable tool for infrared welding pool images segmentation. (C) 2014 Elsevier B.V. All rights reserved.