Towards Mobile OCR: How To Take a Good Picture of a Document Without Sight
Identifieur interne : 000237 ( Pmc/Checkpoint ); précédent : 000236; suivant : 000238Towards Mobile OCR: How To Take a Good Picture of a Document Without Sight
Auteurs : Michael Cutter ; Roberto ManduchiSource :
- Proceedings of the ACM Symposium on Document Engineering. ACM Symposium on Document Engineering ; 2015.
Abstract
The advent of mobile OCR (optical character recognition) applications on regular smartphones holds great promise for enabling blind people to access printed information. Unfortunately, these systems suffer from a problem: in order for OCR output to be meaningful, a well-framed image of the document needs to be taken, something that is difficult to do without sight. This contribution presents an experimental investigation of how blind people position and orient a camera phone while acquiring document images. We developed experimental software to investigate if verbal guidance aids in the acquisition of OCR-readable images without sight. We report on our participant's feedback and performance before and after assistance from our software.
Url:
DOI: 10.1145/2682571.2797066
PubMed: 26677461
PubMed Central: 4677830
Affiliations:
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<front><div type="abstract" xml:lang="en"><p id="P1">The advent of mobile OCR (optical character recognition) applications on regular smartphones holds great promise for enabling blind people to access printed information. Unfortunately, these systems suffer from a problem: in order for OCR output to be meaningful, a well-framed image of the document needs to be taken, something that is difficult to do without sight. This contribution presents an experimental investigation of how blind people position and orient a camera phone while acquiring document images. We developed experimental software to investigate if verbal guidance aids in the acquisition of OCR-readable images without sight. We report on our participant's feedback and performance before and after assistance from our software.</p>
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<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
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<title-group><article-title>Towards Mobile OCR: How To Take a Good Picture of a Document Without Sight</article-title>
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<contrib-group><contrib contrib-type="author"><name><surname>Cutter</surname>
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<aff id="A1">University of California, Santa Cruz,<email>mcutter@soe.ucsc.edu</email>
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<contrib contrib-type="author"><name><surname>Manduchi</surname>
<given-names>Roberto</given-names>
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<aff id="A2">University of California, Santa Cruz,<email>manduchi@soe.ucsc.edu</email>
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<pub-date pub-type="nihms-submitted"><day>28</day>
<month>11</month>
<year>2015</year>
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<pub-date pub-type="ppub"><year>2015</year>
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<pub-date pub-type="pmc-release"><day>14</day>
<month>12</month>
<year>2015</year>
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<volume>2015</volume>
<fpage>75</fpage>
<lpage>84</lpage>
<pmc-comment>elocation-id from pubmed: 10.1145/2682571.2797066</pmc-comment>
<abstract><p id="P1">The advent of mobile OCR (optical character recognition) applications on regular smartphones holds great promise for enabling blind people to access printed information. Unfortunately, these systems suffer from a problem: in order for OCR output to be meaningful, a well-framed image of the document needs to be taken, something that is difficult to do without sight. This contribution presents an experimental investigation of how blind people position and orient a camera phone while acquiring document images. We developed experimental software to investigate if verbal guidance aids in the acquisition of OCR-readable images without sight. We report on our participant's feedback and performance before and after assistance from our software.</p>
</abstract>
<kwd-group><kwd>Visual Impairment</kwd>
<kwd>Optical Character Recognition</kwd>
<kwd>Document Processing</kwd>
</kwd-group>
<kwd-group><title>General Terms</title>
<kwd>Design</kwd>
<kwd>Experimentation</kwd>
<kwd>Human Factors</kwd>
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<name sortKey="Manduchi, Roberto" sort="Manduchi, Roberto" uniqKey="Manduchi R" first="Roberto" last="Manduchi">Roberto Manduchi</name>
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