Real Time License Plate Recognition via Watershed and Viterbi Algorithm

Authors(2) :-Kaushalya Bakde, Suyash Agrawal

License Plate Recognition (LPR) is the extraction of vehicle license plate information from still images or frame sequences (videos). Character segmentation & recognition has long been a critical area of the OCR process. The characters are detected in the order defined by the matching quality. In this paper three main procedures watershed, thresholding and hidden markov model based Viterbi algorithm was used to perform license plate segmentation and recognition tasks. The watershed transformation with thresholding algorithm based on the gradient approach gives good results for segmentation of characters. This is mainly designed for Indian Car license plate. The procedure follows a simple and effective way to segment and recognize the characters. This paper also presents extensive experiments using real video sequences to verify the proposed method.

Authors and Affiliations

Kaushalya Bakde
Computer Science & Engineering Department, Rungta College of Engineering & Technology, Kurud Kohka Bhilai, Chhattisgarh, India
Suyash Agrawal
Computer Science & Engineering Department, Rungta College of Engineering & Technology, Kurud Kohka Bhilai, Chhattisgarh, India

License plate recognition (LPR), Watershed algorithm, Thresholding, Hidden markov , Viterbi algorithm, Optical Character Recognition (OCR) for cars.

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2016
Date of Publication : 2016-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 793-800
Manuscript Number : IJSRSET1623213
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Kaushalya Bakde, Suyash Agrawal, " Real Time License Plate Recognition via Watershed and Viterbi Algorithm, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 3, pp.793-800, May-June-2016.
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