[1] WANG C Q, WANG X F, ZHOU X, et al. The aircraft skin crack inspection based on different-source sensors and support vector machines[J]. Journal of Nondestructive Evaluation, 2016, 35(3):46.
[2] MUMTAZ R, MUMTAZ M, MANSOOR A B, et al. Computer aided visual inspection of aircraft surfaces[J]. International Journal of Image Processing.2012, 6(1):38-53.
[3] LIU M B, LI B B, LI J T, et al. Smart coating sensor applied in crack detection for aircraft[J]. Applied Mechanics and Materials, 2013, 330(6):383-388.
[4] DENG Y, LIU X, UDPA L. Magneto-optic imaging for aircraft skins inspection:a probability of detection study of simulated and experimental image data[J]. IEEE Transactions on Reliability, 2012, 61(4):901-908.
[5] HASNI H, ALAVI A H, JIAO P C, et al. Detection of fatigue cracking in steel bridge girders:a support vector machine approach[J]. Archives of Civil and Mechanical Engineering, 2017(17):609-622.
[6] CHA Y J, CHOI W, BVYVKÖZTVRK O. Deep learning-based crack damage detection using convolutional neural networks[J]. Computer-Aided Civil and Infrastructure Engineering, 2017, 32(5):361-378.
[7] 陈瑶.基于图像分析的桥梁裂缝检测方法研究[D].合肥:中国科学技术大学,2016:1-8.(CHEN Y. Research on the bridge crack detection method based on image analysis[D]. Hefei:University of Science and Technology of China, 2016:1-8.)
[8] 姜吉荣.基于图像分析的路面裂缝检测方法与识别研究[D].南京:南京邮电大学,2016:1-10.(JIANG J R. Research on pavement crack detection and recognition methods based on image analysis[D]. Nanjing:Nanjing University of Posts and Telecommunications, 2016:1-10.)
[9] BAHR B, MAARI S. Robotic-aided system for inspection of aging aircraft:national institute for aviation research[J]. NDT and E International,1992, 25(1):41-42.
[10] 高庆吉,胡丹丹,牛国臣,等.基于磁光图像的飞机铆钉缺陷识别[J].中国图象图形学报,2007,12(12):2179-2183.(GAO Q J, HU D D, NIU G C, et al. Defect recognition of aircraft rivet based on magento-optic image[J]. Journal of Image and Graphics, 2007, 12(12):2179-2183.)
[11] 王耀东,余祖俊,白彪,等.基于图像处理的地铁隧道裂缝识别算法研究[J].仪器仪表学报,2014,35(7):1489-1496.(WANG Y D, YU Z J, BAI B, et al. Research on image processing based subway tunnel crack identification algorithm[J]. Chinese Journal of Scientific Instrument, 2014, 35(7):1489-1496.)
[12] 吴秀永,徐科,徐金梧.基于Gabor小波和核保局投影算法的表面缺陷自动识别方法[J].自动化学报,2010,36(3):438-441.(WU X Y, XU K, XU J W. Automatic recognition method of surface defects based on Gabor wavelet and kernel locality preserving projections[J]. Acta Automatica Sinica, 2010, 36(3):438-441.)
[13] JIN L S, TIAN L, WANG R B, et al. An improved Otsu image segmentation algorithm for path mark detection under variable illumination[C]//IV'2005:Proceedings of the 2005 IEEE Intelligent Vehicles Symposium. Piscataway, NJ:IEEE, 2005:840-844.
[14] MOHAMED H M, MAHMOUD E. Efficient solution of Otsu multilevel image thresholding:a comparative study[J]. Expert Systems with Applications, 2019, 116:299-309.
[15] GOH T Y, BASAH S N, YAZID H, et al. Performance analysis of image thresholding:Otsu technique[J]. Measurement, 2018, 114:298-307.
[16] 薛倩,杨程屹,王化祥.去除椒盐噪声的交替方向法[J].自动化学报,2013,39(12):2071-2076.(XUE Q, YANG C Y, WANG H X. Alternating direction method for salt-and-pepper denoising[J]. Acta Automatica Sinica, 2013, 39(12):2071-2076.) |