Quantitative Characteristics on Defects through Data Processing of Thermal Infrared Imaging
Numerous experiments have demonstrated that infrared thermographic methods are effective for detection of subsurface defects in the materials. The response of the material to the thermal stimulus is dependent on the existence of subsurface defects and their features. In order to obtain the information about defects, the material’s response to the thermal stimulus is studied. In this study, image processing was applied to infrared thermography images to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, thermal images were often not appropriate. Thus, four point method was used for processing of every pixel of thermal images using MATLAB program for quantitative evaluation of defect detection and characterization which increased the infrared non-destructive testing capabilities since subtle defects signature became apparent..