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Handwritten signature verification using hidden Markov models
Thesis (MScEng)--University of Stellenbosch, 2003.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2012
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| _version_ | 1867613733035966464 |
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| access_status_str | Open Access |
| author | Sindle, Colin |
| author2 | Du Preez, J. A. |
| author_browse | Du Preez, J. A. Sindle, Colin |
| author_facet | Du Preez, J. A. Sindle, Colin |
| author_sort | Sindle, Colin |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MScEng)--University of Stellenbosch, 2003. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/53445 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:40:49.380Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2012 |
| publishDateRange | 2012 |
| publishDateSort | 2012 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/53445 Handwritten signature verification using hidden Markov models Sindle, Colin Du Preez, J. A. Herbst, B. M. Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Pattern recognition systems Markov processes Signatures (Writing) Dissertations -- Electronic engineering Theses -- Electronic engineering Thesis (MScEng)--University of Stellenbosch, 2003. ENGLISH ABSTRACT: Handwritten signatures are provided extensively to verify identity for all types of transactions and documents. However, they are very rarely actually verified. This is because of the high cost of training and employing enough human operators (who are still fallible) to cope with the demand. They are a very well known, yet under-utilised biometric currently performing far below their potential. We present an on-line/dynamic handwritten signature verification system based on Hidden Markov Models, that far out performs human operators in both accuracy and speed. It uses only the local signature features-sampled from an electronic writing tablet-after some novel preprocessing steps, and is a fully automated system in that there are no parameters that need to be manually fine-tuned for different users. Novel verifiers are investigated which attain best equal error rates of between 2% and 5% for different types of high quality deliberate forgeries, and take a fraction of a second to accept or reject an identity claim on a 700 MHz computer. AFRIKAANSE OPSOMMING: Geskrewe handtekeninge word gereeld gebruik om die identiteit van dokumente en transaksies te bevestig. Aangesien dit duur is in terme van menslike hulpbronne, word die integrit eit daarvan selde nagegaan. Om handtekeninge deur menslike operateurs te verifieër. is ook feilbaar-lOO% akkurate identifikasie is onrealisties. Handtekeninge is uiters akkurate en unieke identifikasie patrone wat in die praktyk nie naastenby tot hul volle potensiaal gebruik word nie. In hierdie navorsing gebruik ons verskuilde Markov modelle om dinamiese handtekeningherkenningstelsels te ontwikkel wat, in terme van spoed en akkuraatheid heelwat meer effektief as operateurs is. Die stelsel maak gebruik van slegs lokale handtekening eienskappe (en verwerkings daarvan) soos wat dit verkry word vanaf 'n elektroniese skryftablet. Die stelsel is ten volle outomaties en geen parameters hoef aangepas te word vir verskillende gebruikers nie. 'n Paar tipes nuwe handtekeningverifieërders word ondersoek en die resulterende gelykbreekpunt vir vals-aanvaardings- en vals-verwerpingsfoute lê tussen 2% en 5% vir verskillende tipes hoë kwaliteit vervalsde handtekeninge. Op 'n tipiese 700 MHz verwerker word die identiteit van 'n persoon ill minder as i sekonde bevestig. 2012-08-27T11:35:28Z 2012-08-27T11:35:28Z 2003-12 Thesis http://hdl.handle.net/10019.1/53445 en_ZA Stellenbosch University 104 p. : ill. application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Pattern recognition systems Markov processes Signatures (Writing) Dissertations -- Electronic engineering Theses -- Electronic engineering Sindle, Colin Handwritten signature verification using hidden Markov models |
| title | Handwritten signature verification using hidden Markov models |
| title_full | Handwritten signature verification using hidden Markov models |
| title_fullStr | Handwritten signature verification using hidden Markov models |
| title_full_unstemmed | Handwritten signature verification using hidden Markov models |
| title_short | Handwritten signature verification using hidden Markov models |
| title_sort | handwritten signature verification using hidden markov models |
| topic | Pattern recognition systems Markov processes Signatures (Writing) Dissertations -- Electronic engineering Theses -- Electronic engineering |
| url | http://hdl.handle.net/10019.1/53445 |
| work_keys_str_mv | AT sindlecolin handwrittensignatureverificationusinghiddenmarkovmodels |