한국통신학회논문지 (The Journal of Korean Institute of Communications and Information Sciences)

한국통신학회 (The Korean Institute of Commucations and Information Sciences)
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Real-Time Vehicle License Plate Detection Based on Background Subtraction and Cascade of Boosted Classifiers

  • Sarker, Md. Mostafa Kamal (Electronics Convergence Engineering, Wonkwang University) ;
  • Song, Moon Kyou (Electronics Convergence Engineering, Wonkwang University)
  • 투고 : 2014.06.18
  • 심사 : 2014.09.03
  • 발행 : 2014.10.31
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초록

License plate (LP) detection is the most imperative part of an automatic LP recognition (LPR) system. Typical LPR contains two steps, namely LP detection (LPD) and character recognition. In this paper, we propose an efficient Vehicle-to-LP detection framework which combines with an adaptive GMM (Gaussian Mixture Model) and a cascade of boosted classifiers to make a faster vehicle LP detector. To develop a background model by using a GMM is possible in the circumstance of a fixed camera and extracts the motions using background subtraction. Firstly, an adaptive GMM is used to find the region of interest (ROI) on which motion detectors are running to detect the vehicle area as blobs ROIs. Secondly, a cascade of boosted classifiers is executed on the blobs ROIs to detect a LP. The experimental results on our test video with the resolution of $720{\times}576$ show that the LPD rate of the proposed system is 99.14% and the average computational time is approximately 42ms.

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참고문헌

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피인용 문헌

  1. Segmentation and Recognition of Korean Vehicle License Plate Characters Based on the Global Threshold Method and the Cross-Correlation Matching Algorithm pp.2092805X, 2016, https://doi.org/10.3745/JIPS.02.0050