DocumentCode :
3548184
Title :
Automatic arabic number plate recognition
Author :
Abd El Rahman, A. ; Hamdy, A. ; Zaki, F.
Author_Institution :
Sakhr Software, Egypt
fYear :
2013
fDate :
17-19 Dec. 2013
Firstpage :
23
Lastpage :
28
Abstract :
This paper presents a license plate recognition system for the Egyptian plates introduced in 2008. The proposed system is composed of three main stages; localization & skew correction stage, segmentation stage, and recognition stage. The localization stage uses the main feature of the plate where high contrast text-background is tagged with colored or gray area, to find the plate candidates in the image and to measure the skew angle. In segmentation stage, connected component analysis is applied to find objects belong to license number. The objects will be analyzed to attach diacritic and over segmented objects to each other to form a group of recognizable objects. The final objects will be split to digits and letter groups. In recognition stage, an adapted template match technique is introduced to recognize the digits and letter groups separately after normalizing them. The system is tested against a real video of two hours and the accuracy was 81% and average time per frame was 24 msec/frame.
Keywords :
image colour analysis; image matching; image segmentation; Egyptian plates; adaptive template matching technique; automatic Arabic number plate recognition; connected component analysis; high contrast text-background; license plate recognition system; localization-and-skew correction stage; recognition stage; segmentation stage; skew angle measurement; Accuracy; Computers; Image color analysis; Image edge detection; Image segmentation; Licenses; Strips; Egyptian license plate recognition; connected component; template matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Communications and Computers (JEC-ECC), 2013 Japan-Egypt International Conference on
Conference_Location :
6th of October City
Type :
conf
DOI :
10.1109/JEC-ECC.2013.6766379
Filename :
6766379
Link To Document :
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