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https://hdl.handle.net/1959.11/5607
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, C K | en |
dc.contributor.author | Leedham, Graham | en |
dc.date.accessioned | 2010-04-16T14:12:00Z | - |
dc.date.issued | 2004 | - |
dc.identifier.citation | International Journal of Computer Vision, 57(2), p. 107-120 | en |
dc.identifier.issn | 1573-1405 | en |
dc.identifier.issn | 0920-5691 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/5607 | - |
dc.description.abstract | The use of optical character recognition (OCR) has achieved considerable success in the sorting of machine-printed mail. The automatic reading of unconstrained handwritten addresses however, is less successful. This is due to the high error rate caused by the wide variability of handwriting styles and writing implements. This paper describes a strategy for automatic handwritten address reading which integrates a postcode recognition system with a hybrid verification stage. The hybrid verification system seeks to reduce the error rate by correlating the postcode against features extracted and words recognised from the remainder of the handwritten address. Novel use of syntactic features extracted from words has resulted in a significant reduction in the error rate while keeping the recognition rate high. Experimental results on a testset of 1,071 typical Singapore addresses showed a significant improvements from 24.0% error rate, 71.2% correct recognition rate, and 4.8% rejection rate using "raw" OCR postcode recognition to 0.4% error rate, 65.1% correct recognition rate, and 34.5% rejection rate using the hybrid verification approach. The performance of the approach compares favourably with the currently installed commercial system at Singapore Post, which achieved 0.7% error rate, 47.8% correct recognition rate, and 51.5% rejection rate for 6-digit postcode using the same test data. | en |
dc.language | en | en |
dc.publisher | Kluwer Academic Publishers | en |
dc.relation.ispartof | International Journal of Computer Vision | en |
dc.title | A New Hybrid Approach to Handwritten Address Verification | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1023/B:VISI.0000013085.47268.e8 | en |
dc.subject.keywords | Artificial Intelligence and Image Processing | en |
dc.subject.keywords | Computer Vision | en |
dc.subject.keywords | Image Processing | en |
local.contributor.firstname | C K | en |
local.contributor.firstname | Graham | en |
local.subject.for2008 | 080199 Artificial Intelligence and Image Processing not elsewhere classified | en |
local.subject.for2008 | 080106 Image Processing | en |
local.subject.for2008 | 080104 Computer Vision | en |
local.subject.seo2008 | 810199 Defence not elsewhere classified | en |
local.subject.seo2008 | 810107 National Security | en |
local.subject.seo2008 | 890299 Computer Software and Services not elsewhere classified | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | cleedham@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20100415-111943 | en |
local.publisher.place | Netherlands | en |
local.format.startpage | 107 | en |
local.format.endpage | 120 | en |
local.identifier.scopusid | 2142758135 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 57 | en |
local.identifier.issue | 2 | en |
local.contributor.lastname | Lee | en |
local.contributor.lastname | Leedham | en |
dc.identifier.staff | une-id:cleedham | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:5739 | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | A New Hybrid Approach to Handwritten Address Verification | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Lee, C K | en |
local.search.author | Leedham, Graham | en |
local.uneassociation | Unknown | en |
local.year.published | 2004 | en |
Appears in Collections: | Journal Article |
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