Image Segmentation Method for Wheel Set Online Measurement

被引:0
作者
Wu, Kaihua [1 ]
Ban, Tao [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310018, Zhejiang, Peoples R China
来源
FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE, PTS 1-4 | 2011年 / 44-47卷
关键词
Wheel Set Measurement; Image Processing; Image Segmentation; Maximum Histogram Entropy; Genetic Algorithm;
D O I
10.4028/www.scientific.net/AMM.44-47.3854
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Wheel set is the major running components of a train. Online measurement of wheel set wear parameters is important for the safety of train. The acquisition and processing of wheel set profile image is the key problem in an online measuring method based on machine vision. Factors influencing the effect of image acquisition were analyzed. The main factors included environmental illumination, light reflection, CCD exposure time and light source change. An optimal threshold method based on entropy criterion and genetic algorithm for image threshold segmentation was proposed. The optimal threshold was found by iterative analysis. The image segmentation algorithm eliminated effectively the interferences in the image acquisition and extracted wheel set profile curve from varying background. Better segmentation effect ensured the measurement accuracy of wheel set wear parameters.
引用
收藏
页码:3854 / 3858
页数:5
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