Title
Automatic Vehicle Classification System Using Range Sensor
Abstract
This paper presents an Automatic Vehicle Classification System based upon Laser Intensity Images obtained from range sensors (called AVCSLII). Current systems that utilize loop detectors, video cameras, and range sensors have deficiencies. The loop detectors have high failure rates due to pavement failures and poor maintenance. Video based systems and range sensors do not perform well in deteriorated atmospheric conditions (such as rain and fog). The developed generations of image based range sensors offer the promise of sensors that are less sensitive to deteriorated environmental conditions. AVCSLII system extracts features of laser intensity images, produced by laser sensory units. These features are used to train a Neural Network (NN). The AVCSLII system recalls its trained NN for classification of vehicles. This technique outperforms loop detectors, video cameras, and range data techniques in deteriorated environmental conditions. © 2005 IEEE.
Publication Date
1-1-2005
Publication Title
International Conference on Information Technology: Coding and Computing, ITCC
Volume
2
Number of Pages
107-112
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/itcc.2005.96
Copyright Status
Unknown
Socpus ID
24744442584 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/24744442584
STARS Citation
Hussain, Khaled F. and Moussa, Ghada S., "Automatic Vehicle Classification System Using Range Sensor" (2005). Scopus Export 2000s. 4479.
https://stars.library.ucf.edu/scopus2000/4479