DocumentCode :
1353835
Title :
Composite real-time image processing for railways track profile measurement
Author :
Alippi, Cesare ; Casagrande, Ettore ; Scotti, Fabio ; Piuri, Vincenzo
Author_Institution :
Dipt. di Elettronica e Inf., Politecnico di Milano, Italy
Volume :
49
Issue :
3
fYear :
2000
fDate :
6/1/2000 12:00:00 AM
Firstpage :
559
Lastpage :
564
Abstract :
Checking railway status is critical to guarantee high operating safety, proper maintenance schedule, and low maintenance and operating costs. This operation consists of the analysis of the rail profile and level as well as overall geometry and undulation. Traditional detection systems are based on mechanical devices in contact with the track. Innovative approaches are based on laser scanning and image analysis. This paper presents an efficient composite technique for track profile extraction with real-time image processing. High throughput is obtained by algorithmic prefiltering to restrict the image area containing the track profile, while high accuracy is achieved by neural reconstruction of the profile itself
Keywords :
Gaussian distribution; condition monitoring; convolution; generalisation (artificial intelligence); image restoration; maintenance engineering; measurement by laser beam; radial basis function networks; railways; surface topography measurement; CCD cameras; Gaussian distribution; RBF network; algorithmic prefiltering; composite real-time image processing; convolution; generalization; high accuracy; high throughput; laser based measurement; laser scanning; maintenance; neural reconstruction; overall geometry; railway status checking; railway track profile measurement; track profile extraction; undulation; Costs; Fasteners; Geometrical optics; Geometry; Image analysis; Image processing; Image reconstruction; Pollution measurement; Rail transportation; Railway safety;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/19.850395
Filename :
850395
Link To Document :
بازگشت