DocumentCode
2832597
Title
License Plate Extraction Based on Vertical Edge Detection and Mathematical Morphology
Author
Qiu, Youjie ; Sun, Min ; Zhou, Wenling
Author_Institution
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
5
Abstract
License plate recognition plays an important role in intelligent transport system; however, plate region extraction is the key step before the final recognition. In this paper, an effective license plate extraction algorithm based on vertical edge detection and mathematical morphology is proposed, which can exactly extract the plate from complex background. The proposed algorithm mainly consists of two modules: license plate region´s rough detection and license plate accurate detection. The former aims to find out region of interest (ROI) through a sequence of steps including vertical edge detection, edge detection and mathematical morphology, while the latter analyzes the ROI by taking full advantage of outer shape feature and inner texture feature of license plate. Experiments have been conducted for this algorithm. 400 images taken from various scenes were employed, including diverse angles, different lightening conditions, etc. The proposed algorithm can detect the region of license plate quickly with 98.1 percent accuracy.
Keywords
edge detection; feature extraction; mathematical morphology; traffic engineering computing; intelligent transport system; license plate accurate detection; license plate extraction algorithm; license plate recognition; license plate region rough detection; mathematical morphology; plate region extraction; region of interest; vertical edge detection; Automation; Gray-scale; Image edge detection; Image sequence analysis; Image texture analysis; Intelligent systems; Licenses; Morphology; Shape; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5364222
Filename
5364222
Link To Document