doi:10.16186/j.cnki.1673-9787.2019110004

Received:2019/11/01

Revised:2020/05/21

Published:2021/05/15

Grid extraction of railway guardrail based on multi-feature fusion

LAN Zhimin, LIANG Liming, SHENG Xiaoqi, LI Fuquan, WU jian

School of Electrical Engineering and Automation， Jiangxi University of Science and Technology， Ganzhou 341000 ， Jiangxi， China

Abstract:Railway guardrail is the necessary guarantee for the safe operation of trains at high speed from foreign body intrusion， the accurate extraction of its image is the key step of railway infrastructure automatic detection. Aiming at the problem that railway guardrail image is difficult to accurately extract because of background interference factor， a grid extraction algorithm of railway guardrail fusing multiple features and two-dimensional maximum entropy was proposed. Firstly， the railway guardrail image was denoised by bilateral filtering and enhanced by gamma transform. Then， the linear feature， variance feature and moment feature of the guardrail were extracted separately. The initial segmentation of the feature maps were obtained respectively by employing two-dimensional maximum entropy. Finally， the weighted fusion and connected domain denoising were applied according to the initial segmentation results. The experimental results indicated that the proposed algorithm was robust to the extraction of railway guardrail grid.

Key words:railway guardrail;grid extraction;feature extraction;two-dimensional maximum entropy;connected domain denoising

 基于多特征融合的铁路护栏网格提取_蓝智敏.pdf