[1] Feng Q, Chen W R, Wang Y L et al. Research on the algorithm to measure the pantographic slipper abrasion[J]. Journal of the China Railway Society, 32, 109-113(2010).
[2] Sun F H. Design of upper-computer software and handling for measurement system of pantograph slide plate's abrasion[D]. Chengdu: Southwest Jiaotong University(2011).
[3] Lu S F, Liu Z. A fast alignment method in sequence images of multiple units train[J]. Acta Optica Sinica, 37, 0915002(2017).
[4] Lu S F, Liu Z. Image comparison and analysis of trouble of moving EMU[J]. Laser & Optoelectronics Progress, 54, 091503(2017).
[5] Zou R, Li J K, Xu J X et al. Deflection fault detection for locking plate of freight trains under complex scene[J]. Journal of Railway Science and Engineering, 12, 917-922(2015).
[6] Li T T, Yang F, Xu X L. Method of large-scale measurement based on multi-vision line structured light sensor[J]. Chinese Journal of Lasers, 44, 1104003(2017).
[7] Zhou L, Yang N. Image scratch detection research based on adaptive binary tree[J]. Laser & Optoelectronics Progress, 52, 051002(2015).
[8] Shen H, Li S M, Bo F C et al. On road vehicles real-time detection and tracking using vision based approach[J]. Acta Optica Sinica, 30, 1076-1083(2010).
[9] Zhang G J[J]. Vision measurement(2008).
[10] Sobel I E. Camera models and machine perception[D]. Palo Alto: Stanford University(1970).
[12] Luo P, Wang Z Y, Gao X R et al. Abrasion detection of pantographic slipper when locomotive entering warehouse[J]. Opto-Electronic Engineering, 31, 88-90(2004).
[13] Tu X B. Research of pantogtaph wear detection system based on machine vision[D]. Guangzhou: Guangdong University of technology(2013).
[15] Dollár P, Zitnick C L. Structured forests for fast edge detection[C]. IEEE International Conference on Computer Vision, 1841-1848(2013).