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dc.contributor.authorNazemi, Azadeh
dc.contributor.authorMurray, Iain
dc.contributor.authorMcMeekin, David
dc.date.accessioned2017-01-30T11:20:56Z
dc.date.available2017-01-30T11:20:56Z
dc.date.created2015-04-29T20:00:36Z
dc.date.issued2014
dc.identifier.citationNazemi, A. and Murray, I. and McMeekin, D. 2014. Practical Segmentation Methods for Logical and Geometric Layout Analysis to Improve Scanned PDF Accessibility to Vision Impaired. International Journal of Signal Processing, Image Processing and Pattern Recognition. 7 (4): pp. 23-26.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/10775
dc.identifier.doi10.14257/ijsip.2014.7.4.03
dc.description.abstract

The use of electronic documents has rapidly increased in recent decades and the PDF is one the most commonly used electronic document formats. A scanned PDF is an image and does not actually contain any text. For the vision–impaired user who is dependent upon a screen reader to access this information, this format is not useful. Thus addressing PDF accessibility through assistive technology has now become an important concern. PDF layout analysis provides precious formatting information that supports PDF component classification. This classification facilitates the tag generation. Accurate tagging produces a searchable and navigable scanned PDF document. This paper describes several practical segmentation methods which are easy to implement and efficient for PDF layout analysis so that the scanned PDF document can be navigated or searched using assistive technologies.

dc.publisherSERSC Science & Engineering Research Support Society
dc.subjectOptical character recognition (OCR)
dc.subjectVision-impaired
dc.subjectPDF layout analysis
dc.titlePractical Segmentation Methods for Logical and Geometric Layout Analysis to Improve Scanned PDF Accessibility to Vision Impaired
dc.typeJournal Article
dcterms.source.volume7
dcterms.source.number4
dcterms.source.startPage23
dcterms.source.endPage26
dcterms.source.issn2005-4254
dcterms.source.titleInternational Journal of Signal Processing, Image Processing and Pattern Recognition
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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