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Kim, K.K., Kim, K.I., Kim, J.B. and Kim, H.J. (2000) Learning-Based Approach for License Plate Recognition. Proceedings of the IEEE Signal Processing Society Workshop: Neural Networking for Signal Processing X, Sydney, 11-13 December 2000, 614-623. http://dx.doi.org/10.1109/NNSP.2000.890140

has been cited by the following article:

• TITLE: Variance Window Based Car License Plate Localization

  AUTHORS: Jing Pang

  KEYWORDS: Harr Wavelet, Black Top-Hat, Binarization, Moving Window, Variance Score

  JOURNAL NAME: Journal of Computer and Communications, Vol.2 No.9, July 11, 2014

  ABSTRACT: In this paper, a new method for discovering the candidate car license plate locations is presented. First, the image is decomposed using a Haar wavelet to get the HL band with vertical edges. Then, the HL band image is binarized using an Otsu threshold. Next a black top-hat algorithm is applied to reduce the effects of interfering large continuous features other than the license plate. At this time, a moving window based modified variance score calculation is made for areas with white pixels. This work found that the top 3 detected rectangle windows correctly locate the license plate regions with a success rate of about 98.2%. Moreover, the proposed method is robust enough to locate the plates in cases where the rough vehicle position has not been previously discovered and the cars are not centered in the image.