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Hidden Markov models for robust recognition of vehicle licence plates
Dissertation (MEng (Computer Engineering))--University of Pretoria, 2002.
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| Format: | Thesis |
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University of Pretoria
2013
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| _version_ | 1867613644227870720 |
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| access_status_str | Open Access |
| author2 | Botha, Elizabeth C. |
| author_browse | Botha, Elizabeth C. |
| author_facet | Botha, Elizabeth C. |
| collection | Thesis |
| dc_rights_str_mv | © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MEng (Computer Engineering))--University of Pretoria, 2002. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/29402 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:39:25.358Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/29402 Hidden Markov models for robust recognition of vehicle licence plates Botha, Elizabeth C. upetd@up.ac.za Van Heerden, Renier Pelser Automobile licence plates Pattern perception Automobile licence plates markov analysis Robust control UCTD Dissertation (MEng (Computer Engineering))--University of Pretoria, 2002. In this dissertation the problem of recognising vehicle licence plates of which the sym¬bols can not be segmented by standard image processing techniques is addressed. Most licence plate recognition systems proposed in the literature do not compensate for dis¬torted, obscured and damaged licence plates. We implemented a novel system which uses a neural network/ hidden Markov model hybrid for licence plate recognition. We implemented a region growing algorithm, which was shown to work well when used to extract the licence plate from a vehicle image. Our vertical edges algorithm was not as successful. We also used the region growing algorithm to separate the symbols in the licence plate. Where the region growing algorithm failed, possible symbol borders were identified by calculating local minima of a vertical projection of the region. A multilayer perceptron neural network was used to estimate symbol probabilities of all the possible symbols in the region. The licence plate symbols were the inputs of the neural network, and were scaled to a constant size. We found that 7 x 12 gave the best character recognition rate. Out of 2117 licence plate symbols we achieved a symbol recognition rate of 99.53%. By using the vertical projection of a licence plate image, we were able to separate the licence plate symbols out of images for which the region growing algorithm failed. Legal licence plate sequences were used to construct a hidden Markov model contain¬ing all allowed symbol orderings. By adapting the Viterbi algorithm with sequencing constraints, the most likely licence plate symbol sequences were calculated, along with a confidence measure. The confidence measure enabled us to use more than one licence plate and symbol segmentation technique. Our recognition rate increased dramatically when we com¬bined the different techniques. The results obtained showed that the system developed worked well, and achieved a licence plate recognition rate of 93.7%. Electrical, Electronic and Computer Engineering unrestricted 2013-09-07T15:35:19Z 2005-11-21 2013-09-07T15:35:19Z 2002-04-01 2002 2005-11-11 Dissertation Van Heerden, RP 2002, Hidden Markov models for robust recognition of vehicle licence plates, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/29402 > H614/ag http://hdl.handle.net/2263/29402 http://upetd.up.ac.za/thesis/available/etd-11112005-161130/ © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | Automobile licence plates Pattern perception Automobile licence plates markov analysis Robust control UCTD Hidden Markov models for robust recognition of vehicle licence plates |
| title | Hidden Markov models for robust recognition of vehicle licence plates |
| title_full | Hidden Markov models for robust recognition of vehicle licence plates |
| title_fullStr | Hidden Markov models for robust recognition of vehicle licence plates |
| title_full_unstemmed | Hidden Markov models for robust recognition of vehicle licence plates |
| title_short | Hidden Markov models for robust recognition of vehicle licence plates |
| title_sort | hidden markov models for robust recognition of vehicle licence plates |
| topic | Automobile licence plates Pattern perception Automobile licence plates markov analysis Robust control UCTD |
| url | http://hdl.handle.net/2263/29402 http://upetd.up.ac.za/thesis/available/etd-11112005-161130/ |