Defects’ geometric feature recognition based on infrared image edge detection |
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| Affiliation: | 1. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, PR China;2. School of Mechanical Engineering, Hei Longjiang University of Science and Technology, Harbin 150022, PR China;1. CONSTRUCT-LFC, Faculty of Engineering (FEUP), University of Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal;2. CI&DETS – Polytechnic Institute of Viseu, School of Technology and Management, Department of Civil Engineering, Campus Politécnico de Repeses, 3504-510 Viseu, Portugal;1. School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin 150022, PR China;2. School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, PR China;3. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, PR China;1. Civil Engineering, College of Engineering and Informatics, National University of Ireland, Galway, Ireland;2. Department of Environmental Engineering, Cracow University of Technology, Cracow, Poland;1. School of Light Industry, Harbin University of Commerce, Harbin, 150028, PR China;2. School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, PR China;1. State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an, China;2. Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China;3. Faculty of Mechanical - Electrical and Computer Engineering, School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Vietnam |
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| Abstract: | Edge detection is an important technology in image segmentation, feature extraction and other digital image processing areas. Boundary contains a wealth of information in the image, so to extract defects’ edges in infrared images effectively enables the identification of defects’ geometric features. This paper analyzed the detection effect of classic edge detection operators, and proposed fuzzy C-means (FCM) clustering-Canny operator algorithm to achieve defects’ edges in the infrared images. Results show that the proposed algorithm has better effect than the classic edge detection operators, which can identify the defects’ geometric feature much more completely and clearly. The defects’ diameters have been calculated based on the image edge detection results. |
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| Keywords: | Geometric feature Recognition Infrared image FCM Edge detection |
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