TY - JOUR
T1 - 数字细节增强技术在脉冲热成像无损检测中的应用
AU - Xu, Chao
AU - Chen, Yihe
N1 - Publisher Copyright:
© 2018, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.
PY - 2018/11/25
Y1 - 2018/11/25
N2 - Pulsed thermographic image has the disadvantages of low -contrast, fuzzy -edge, and non -uniformity of illumination for the defect detection, thus, a defect determination method which combines digital detail enhancement (DDE) technology with maximum entropy multi -threshold segmentation method was proposed for the improvement of pulsed thermographic image. Firstly, the contrast between defects and the background was improved significantly after the image was processed with digital detail enhancement algorithm optimized with adaptive contrast enhancement (ACE) algorithm, and reducing the influence of illuminative non -uniformity on defect recognition. Secondly, the target defects with maximum entropy multi -threshold segmentation method optimized with genetic algorithm, and the contours of each defect with eight neighborhood method to get the contour pixels in a certain sequence. Finally, based on the sequential contour pixels, the perimeter and the area of each defect could be estimated respectively with Euclidean distances formula and Green's theorem. The experimental result shows that this method is feasible to estimate defect size quantitatively, and digital detail enhancement technology could improve the defect detectability of pulsed thermographic system in a certain extent.
AB - Pulsed thermographic image has the disadvantages of low -contrast, fuzzy -edge, and non -uniformity of illumination for the defect detection, thus, a defect determination method which combines digital detail enhancement (DDE) technology with maximum entropy multi -threshold segmentation method was proposed for the improvement of pulsed thermographic image. Firstly, the contrast between defects and the background was improved significantly after the image was processed with digital detail enhancement algorithm optimized with adaptive contrast enhancement (ACE) algorithm, and reducing the influence of illuminative non -uniformity on defect recognition. Secondly, the target defects with maximum entropy multi -threshold segmentation method optimized with genetic algorithm, and the contours of each defect with eight neighborhood method to get the contour pixels in a certain sequence. Finally, based on the sequential contour pixels, the perimeter and the area of each defect could be estimated respectively with Euclidean distances formula and Green's theorem. The experimental result shows that this method is feasible to estimate defect size quantitatively, and digital detail enhancement technology could improve the defect detectability of pulsed thermographic system in a certain extent.
KW - Defect measurement
KW - Digital detail enhancement
KW - Multi-threshold maximum entropy
KW - Pulsed thermography
UR - http://www.scopus.com/inward/record.url?scp=85059056600&partnerID=8YFLogxK
U2 - 10.3788/IRLA201847.1104005
DO - 10.3788/IRLA201847.1104005
M3 - 文章
AN - SCOPUS:85059056600
SN - 1007-2276
VL - 47
JO - Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
JF - Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
IS - 11
M1 - 1104005
ER -