DocumentCode
2313454
Title
Vehicle Detection and Shape Recognition Using Optical Sensors: A Review
Author
Atiq, Hafiz Muhammad ; Farooq, Umar ; Ibrahim, Rabbia ; Khalid, Oneeza ; Amar, Muhammad
Author_Institution
Dept. of Electr. Eng., Univ. of The Punjab, Lahore, Pakistan
fYear
2010
fDate
9-11 Feb. 2010
Firstpage
223
Lastpage
227
Abstract
Optical systems are well suited for traffic observation and management. The real-time requirements can be met by implementation of appropriate image processing algorithms in hardware. Being one of the most important applications of optical sensors, vision-based vehicle detection and shape recognition for collecting information about road congestion, for driver assistance and for providing information for future development of roads has received considerable attention over the last one-two decades. There are many reasons for the intense research in this field including security requirements in the countries, the increased number of road accidents, the increased number of vehicles on the roads and the availability of feasible computer technologies that has brought a tremendous progress for computer vision research. This paper provides a critical survey of recent vision based road vehicle detection and shape recognition systems appeared in the literature.
Keywords
computer vision; optical sensors; road vehicles; shape recognition; traffic information systems; computer vision; image processing; optical sensor; road vehicle detection; shape recognition; traffic management; traffic observation; Computer security; Computer vision; Hardware; Image processing; Information security; Optical sensors; Road accidents; Road vehicles; Shape; Vehicle detection; optical sensors; shape recognition; traffic management; vehicle detetction;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Computing (ICMLC), 2010 Second International Conference on
Conference_Location
Bangalore
Print_ISBN
978-1-4244-6006-9
Electronic_ISBN
978-1-4244-6007-6
Type
conf
DOI
10.1109/ICMLC.2010.73
Filename
5460737
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