Defects’ geometric feature recognition based on infrared image edge detection

• Defects’ edge detection effect of classic edge detection operators was analyzed.
• FCM-Canny operator algorithm was proposed and to achieve defects’ edges.
• The proposed algorithm has better effect than the classic edge detection operators.
• The defects’ diameters have been calculated based on the image edge detection results.

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.