Vehicle License Plate Detection in Road Images 


Vol. 43,  No. 2, pp. 186-195, Feb.  2016


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  Abstract

This paper proposes a vehicle license plate detection method in real road environments using 8 bit-MCT features and a landmark-based Adaboost method. The proposed method allows identification of the potential license plate region, and generates a saliency map that presents the license plate’s location probability based on the Adaboost classification score. The candidate regions whose scores are higher than the given threshold are chosen from the saliency map. Each candidate region is adjusted by the local image variance and verified by the SVM and the histograms of the 8bit-MCT features. The proposed method achieves a detection accuracy of 85% from various road images in Korea and Europe.


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  Cite this article

[IEEE Style]

K. Lim, H. Byun, Y. Choi, "Vehicle License Plate Detection in Road Images," Journal of KIISE, JOK, vol. 43, no. 2, pp. 186-195, 2016. DOI: .


[ACM Style]

Kwangyong Lim, Hyeran Byun, and Yeongwoo Choi. 2016. Vehicle License Plate Detection in Road Images. Journal of KIISE, JOK, 43, 2, (2016), 186-195. DOI: .


[KCI Style]

임광용, 변혜란, 최영우, "도로주행 영상에서의 차량 번호판 검출," 한국정보과학회 논문지, 제43권, 제2호, 186~195쪽, 2016. DOI: .


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