DocumentCode :
3478369
Title :
License Plate Recognition Based On Prior Knowledge
Author :
Gao, Qian ; Wang, Xinnian ; Xie, Gongfu
Author_Institution :
Dalian Maritime Univ., Dalian
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
2964
Lastpage :
2968
Abstract :
In this paper, a new algorithm based on improved BP (back propagation) neural network for Chinese vehicle license plate recognition (LPR) is described. The proposed approach provides a solution for the vehicle license plates (VLP) which were degraded severely. What it remarkably differs from the traditional methods is the application of prior knowledge of license plate to the procedure of location, segmentation and recognition. Color collocation is used to locate the license plate in the image. Dimensions of each character are constant, which is used to segment the character of VLPs. The layout of the Chinese VLP is an important feature, which is used to construct a classifier for recognizing. The experimental results show that the improved algorithm is effective under the condition that the license plates were degraded severely.
Keywords :
backpropagation; character recognition; image classification; image colour analysis; image segmentation; neural nets; Chinese vehicle license plate recognition; back propagation neural network; color collocation; license plate classification; license plate segmentation; prior knowledge; Automation; Automotive engineering; Cameras; Character recognition; Degradation; Image segmentation; Licenses; Logistics; Neural networks; Vehicles; License plate recognition; neural network; prior knowledge; vehicle license plates;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4339089
Filename :
4339089
Link To Document :
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