Algorithm of Fuzzy Matching for Redundancies of Rail Surface Images

WANG Yao-na, YIN Xun-shuai, HE Zhen-dong, MU Xue-feng

Abstract

 In order to address the redundancy of image in the detection process of rail surface defects, an algorithm of matching for the redundancies of rail surface images was proposed. At the beginning, the rail surface area was extracted by using the vertical projection method. And then, the location information of defects was obtained through the image preprocess and binarization on the rail surface. Next, the morphological information of the rail surface defects was achieved in the horizontal projection method. At last, the defect location information and morphological information were matched on the basis of the improved fuzzy matching algorithm. The experiment results verify that this algorithm can effectively identify the redundancy information of image, and the accuracy rate is as high as 97.5%.

 

 

Keywords: machine vision,  rail, surface defects,  fuzzy matching


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References


ZHOU Qing-yue. ZHOU Zhen-guo. Research and drafting technical conditions of rail for passenger dedicated Line[C]//China Railway Society. The Proceedings of Technical Seminars for Passenger Dedicated bine Construction. Beijing; Press of Yangtze River.2005s91— 95. (In Chinese)

PAPAELIAS M, LUGG M C, ROBERTS C, et al. Highspeed inspection of rails using ACFM techniques[J]. NDT& E International .2009, 12(4): 328 —335.

TANG Xiang-na. WANG Yao-nan. Visual inspection and classification algorithm of rail surface defect [J]. Computer Engineering.2013. 39(3):25 — 30. (In Chinese)

PAPAELIAS M, ROBERTS C. DAVIS C. A review on nondestructive valuation of rails: state-of-the-art and future deveIopment [J]. Rail and Rapid Transit. 2008. 222(4 ): 367 — 384.

BREYSSE D. Nondestructive evaluation of concrete strength: An historical review and a new perspective by combining NDT methods[J]. Construction and Building Materials.2012.33:139 -163.

НЕ Zhen-Dong. WANG Yao-Nan. МАО Jian-Xu. et al. Research on inverse P-M diffusion-based rail surface defect detection [J]. Acta Automatica Sinica. 2014 . 40(8): 1667— 1679. (In Chinese)

XIAO Chang-yan. JIA Kang-cheng. WANG Yao-nan. Imaging and detection of rail surface defects based on line scanning [J]. Journal of ilunan University: Natural Sciences. 2013. 10 (11):64 — 69. (In Chinese)

LI Qing-yong. KEN Sheng-wei. A real-time visual inspection system for discrete surface defects of rail heads [J]. IEEE Transactions on Instrumentation and Measurement. 2012. 61 (8):2189 —2199.

TANG Z J. ZHANG X Q. DAI Y M. Perceptual image hashing using local entropies and DWT[J], Imaging Science Journal, 2013.16(2):211 — 251.

НIКОТA К. PEDRYCZ W. Matching fuzzy quantities [J]. IEEE Transactions on Systems. Man. and Cybernetics.2002. 21(6): 1580-1586.

CHEN Liu-kui. ZHENG Hong. Finger vein image recognition based on tri-value template fuzzy matching [J]. Geomatics and Information Science of Wuhan University, 2011. 36( 2): 57 — 62.

WANG Y, ZHAI H C, MU G G. Fuzzy matching of images based on shape description matrix[J], Acta Physica Sinica. 2005.54(5): 1965-1968.


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