DocumentCode :
612877
Title :
Degraded License Plate Recognition system for town buses on highway
Author :
Bing-Fei Wu ; Hao-Yu Huang ; Yen-Lin Chen ; Hsin-Yu Lin ; Tsu-Tian Lee ; Chao-Jung Chen
Author_Institution :
Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fYear :
2013
fDate :
10-12 April 2013
Firstpage :
446
Lastpage :
450
Abstract :
This study presented a Degraded License Plate Recognition (DLPR) to identify town buses on highway. Since the License Plates (LPs) of town buses are influenced by the external conditions and become hardly distinguished by the Optical Character Recognition (OCR) method. The proposed DLPR system adopts Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM)-for classification-based solution. The proposed system implements a two-level LPR, including LP localization and character recognition. For the recognition efficiency of the proposed system, two trained databases for LP localization and character recognition are reduced by the mathematical and feature-based approaches, respectively, and thus the searching time can be saved significantly. To certify the performance of recognizing the degraded LPs, the proposed system is demonstrated by physical degraded LP images, and thus the results reveal that the proposed system overcomes several degraded LP images with reasonable recognition accuracy.
Keywords :
image classification; object recognition; road vehicles; statistical analysis; support vector machines; traffic engineering computing; DLPR system; HOG; LP localization; OCR method; SVM; classification-based solution; degraded license plate recognition system; feature-based approach; highway; histogram-of-oriented gradient; mathematical approach; optical character recognition; physical degraded LP image; recognition accuracy; support vector machine; town bus; Character recognition; Databases; Image recognition; Licenses; Support vector machine classification; Vectors; Histogram of Oriented Gradient (HOG); License Plate Recognition; Pattern Recognition; Support Vector Machine (SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on
Conference_Location :
Evry
Print_ISBN :
978-1-4673-5198-0
Electronic_ISBN :
978-1-4673-5199-7
Type :
conf
DOI :
10.1109/ICNSC.2013.6548780
Filename :
6548780
Link To Document :
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