DocumentCode :
2597816
Title :
A new vertical edge detection algorithm and its application
Author :
Al-Ghaili, Abbas M. ; Mashohor, Syamsiah ; Ismail, Alyani ; Ramli, Abdul Rahman
Author_Institution :
Dept. of Comput. & Commun. Syst., Univ. Putra Malaysia, Serdang
fYear :
2008
fDate :
25-27 Nov. 2008
Firstpage :
204
Lastpage :
209
Abstract :
Edge detection is a very important process for many image processing applications, especially in Car License Plate Detection and Recognition Systems(CLPDRS). The need to distinguish the desired details is a very important pre-process in order to give good results in short time processing. We proposed a new and fast vertical edge detection algorithm (VEDA) which is based on the contrast between the gray scale values. Once, input gray image was binarized by using adaptive threshold, unwanted lines elimination algorithm (ULEA) was proposed and applied. After that, a VEDA was applied for experimental images. Then, implementation on the application is performed and discussed in order to confirm that VEDA is robust for highlighting license plate details easily. The results revealed accurate edge detection performance and demonstrated the great efficiency of using VEDA in order to highlight license plate details. Finally, VEDA showed that it is faster than Sobel operator by about 7-9 times.
Keywords :
edge detection; object detection; object recognition; CLPDRS; Sobel operator; adaptive threshold; car license plate detection systems; car license plate recognition systems; gray image; image processing applications; unwanted lines elimination algorithm; vertical edge detection algorithm; Application software; Data mining; Displays; Feature extraction; Image edge detection; Image processing; Image recognition; Licenses; Robustness; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering & Systems, 2008. ICCES 2008. International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-2115-2
Electronic_ISBN :
978-1-4244-2116-9
Type :
conf
DOI :
10.1109/ICCES.2008.4772997
Filename :
4772997
Link To Document :
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