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http://dx.doi.org/10.7840/kics.2012.37A.9.780

License Plates Detection Using a Gaussian Windows  

Kang, Yong-Seok (한국폴리텍대학 자동차학과)
Bae, Cheol-Soo (관동대학교 전자통신공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.37A, no.9, 2012 , pp. 780-785 More about this Journal
Abstract
In the current study, the authors propose a method for extracting license plate regions by means of a neural network trained to output the plates center of gravity. The method is shown to be effective. Since the learning pattern presentation positions are defined by random numbers, a different pattern is submitted to the neural network for learning each time, which enables it to form a neural network with high universality of coverage. The article discusses issues of the optimal learning surface for a license plate covered by the learning pattern, the effect of suppression learning of the number and headlight sections, as well as the effect of learning pattern enlargement/reduction and of concentration value conversion. Results of evaluation tests based on pictures of 595 vehicles taken at an underground parking garage demonstrated detection rates of 98.5%.
Keywords
Projection Summing; Gaussian window; Suppression learning; Artificial Neural Network; License Plates;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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