GPU Accelerated Number Plate Localization in Crowded Situation

(1) Adhi Prahara Mail (Universitas Ahmad Dahlan, Indonesia)
(2) * Andri Pranolo Mail (Universitas Ahmad Dahlan, Indonesia)
(3) Rafał Dreżewski Mail (AGH University of Science and Technology, Poland)
*corresponding author

Abstract


Number Plate Localization (NPL) has been widely used as part of Automatic Number Plate Recognition (ANPR) system. NPL method determines the accuracy of ANPR system. Although it is a mature research, the challenge stills persist especially in crowded situation where many vehicles present. Therefore, a method is proposed to localize number plate in crowded situation. The proposed NPL method uses vertical edge density to extract potential region of number plate then detect the number plate using combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM). The method employs GPU to deal with multiple number plate detection, to handle multi-scale detection window, and to perform real time detection. The test result shows good results, 0.9883 value of AUC (Area Under Curve), and 0.9362 of BAC (Balance Accuracy). Moreover, potential real time detection is foreseen because total process is executed in less than 50 ms. Errors are mainly caused by background that contain letters, non-standard number plate and highly covered number plate

Keywords


Number Plate; Plate Localization; Vertical Edge Detection; HOG; SVM; GPU

   

DOI

https://doi.org/10.26555/ijain.v1i3.46
      

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References


M. Zahedi and S. M. Salehi, "License Plate Recognition System Based on SIFT Features," in World Conference on Information Technology, Istanbul, 2011.

V. Mai, D. Miao, R. Wang and H. Zhang, "An improved method for Vietnam License Plate location," in 2011 International Conference on Multimedia Technology (ICMT), Hangzhou, 2011.

P. Tarabek, "Fast license plate detection based on edge density and integral edge image," in 2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI), Herl'any, 2012.

A. M. Al-Ghaili, S. Mashohor, A. R. Ramli and A. Ismail, "Vertical-Edge-Based Car-License-Plate Detection Method," IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 26 - 38, 03 October 2012.

M. M. Dehshibi and R. Allahverdi, "Persian vehicle license plate recognition using multiclass Adaboost," International Journal of Computer and Electrical Engineering, vol. 4, no. 3, pp. 355 - 358, June 2012.

B. B. Singh and V. H. Deepthi, "Survey on Automatic Vehicle Number Plate Localization," International Journal of Computer Applications, vol. 67, no. 23, pp. 7 - 12, 2013.

N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, CA, USA, 2005.

D. F. Llorca, R. Arroyo and M. A. Sotelo, "Vehicle logo recognition in traffic images using HOG features and SVM," in 2013 16th International IEEE Conference on Intelligent Transportation Systems - (ITSC), The Hague, 2013.

J. Fung and S. Mann, "Using graphics devices in reverse: GPU-based Image Processing and Computer Vision," in 2008 IEEE International Conference on Multimedia and Expo, Hannover, 2008.

C.-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines," ACM Transactions on Intelligent Systems and Technology (TIST), vol. 2, no. 3, p. No. 27, 2011.

C. G. Weng and J. Poon, "A new evaluation measure for imbalanced datasets," in Proceedings of the 7th Australasian Data Mining Conference (AusDM '08), Darlinghurst, Australia, 2008.




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International Journal of Advances in Intelligent Informatics
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Organized by Informatics Department - Universitas Ahmad Dahlan , and UTM Big Data Centre - Universiti Teknologi Malaysia
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