Text Retrieval from Scanned Forms Using Optical Character Recognition

Aggarwal, Vaishali; Jajoria, Sourabh; Sood, Apoorvi

doi:10.1007/978-981-10-6614-6_21

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…In all scanning apps tested, the background surface was not corrected, leading to paper or whiteboard imperfections appearing in the final output. Document scanning now focuses on detection of documents in images [1][2][3] and content recognition [4,5] -typically Optical Character Recognition (OCR) for text -but the problem of highquality capture has not been fully solved. Available apps such as Microsoft Office Lens, Google PhotoScan, Cam Scanner, Adobe Scan, Scanbot and others, produce high-quality results but are sensitive to capture conditions, retain surface imperfections, require manual intervention and often have slow or difficult to use user interfaces.…”

Section: Introductionmentioning

confidence: 99%

CleanPage: Fast and Clean Document and Whiteboard Capture

Courtney¹

2020

Preprint

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The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for high-quality digitization of content from pages and whiteboards to sharable online material. But capturing this information is not always easy, nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop and clean an image of a page or whiteboard. Unlike equivalent systems, no user intervention is required during processing and the result is a high-contrast, low-noise image with a clean homogenous background. Results are presented for a selection of scenarios showing the versatility of the design. CleanPage is compared with two market leader scanning apps using two testing approaches: real paper scans and ground-truth comparisons. These comparisons are achieved by a new testing methodology that allows scans to be compared to unscanned counterparts, by using synthesized images. Real paper scans are tested using image quality measures. An evaluation of standard image quality assessments is included in this work and a novel quality measure for scanned images is proposed and validated. The user experience for each scanning app is assessed, showing CleanPage to be fast and easier to use.

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Section: Introductionmentioning

confidence: 99%

CleanPage: Fast and Clean Document and Whiteboard Capture

Courtney¹

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Document scanning now focuses on the detection of documents in images [ 1 , 2 , 3 ] and content recognition [ 4 , 5 ]—typically Optical Character Recognition (OCR) for text—but the problem of high-quality capture has not been fully solved. Available apps such as Microsoft Office Lens, Google PhotoScan, Cam Scanner, Adobe Scan, Scanbot and others produce high-quality results but are sensitive to capture conditions, retain surface imperfections, require manual intervention, and often have slow or difficult to use user interfaces.…”

Section: Introductionmentioning

confidence: 99%

CleanPage: Fast and Clean Document and Whiteboard Capture

Courtney

2020

J. Imaging

View full text Add to dashboard Cite

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and clean an image of a page or whiteboard. Unlike equivalent systems, no user intervention is required during processing, and the result is a high-contrast, low-noise image with a clean homogenous background. Results are presented for a selection of scenarios showing the versatility of the design. CleanPage is compared with two market leader scanning apps using two testing approaches: real paper scans and ground-truth comparisons. These comparisons are achieved by a new testing methodology that allows scans to be compared to unscanned counterparts by using synthesized images. Real paper scans are tested using image quality measures. An evaluation of standard image quality assessments is included in this work, and a novel quality measure for scanned images is proposed and validated. The user experience for each scanning app is assessed, showing CleanPage to be fast and easier to use.

show abstract