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optical character recognition flexi capture  (ABBYY USA Software House Inc)

 
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    Structured Review

    ABBYY USA Software House Inc optical character recognition flexi capture
    Optical Character Recognition Flexi Capture, supplied by ABBYY USA Software House Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/optical+character+recognition+function/optical+character+recognition+flexi+capture/ppr0468564-35-18-23
    Average 90 stars, based on 1 article reviews
    optical character recognition flexi capture - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: Perinatal outcomes in twin late preterm pregnancies: results from an Italian area-based, prospective cohort study
    Article Snippet: At the Data Managing Center (Modena Policlinico Hospital, University of Modena, and Reggio Emilia) research associates used optical character recognition technology (Flexi Capture, Abbyy®, Germany) to scan the data collection sheets, extract pertinent data, and organize it in a password protected database.

    Article Title: Perinatal outcomes in twin late preterm pregnancies: results from an Italian area-based, prospective cohort study.
    Article Snippet: At the Data Managing Center (Modena Policlinico Hospital, University of Modena, and Reggio Emilia) research associates used optical character recognition technology (Flexi Capture, Abbyy ®, Germany) to scan the data collection sheets, extract pertinent data, and organize it in a password protected database.



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    Example output of fiducial and label detection. The blue color component is shown, with boxed connected components in yellow. The fiducial locations are indicated as cyan and magenta asterisks. Letter labels, as output from the letter <t>recognition</t> function, are shown above the image patch in magenta. Here, all labels are correct except for “N”, which is mislabeled as “M”.
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    Image Search Results


    Example output of fiducial and label detection. The blue color component is shown, with boxed connected components in yellow. The fiducial locations are indicated as cyan and magenta asterisks. Letter labels, as output from the letter recognition function, are shown above the image patch in magenta. Here, all labels are correct except for “N”, which is mislabeled as “M”.

    Journal: Proceedings of SPIE--the International Society for Optical Engineering

    Article Title: Textual fiducial detection in breast conserving surgery for a near-real time image guidance system

    doi: 10.1117/12.2550662

    Figure Lengend Snippet: Example output of fiducial and label detection. The blue color component is shown, with boxed connected components in yellow. The fiducial locations are indicated as cyan and magenta asterisks. Letter labels, as output from the letter recognition function, are shown above the image patch in magenta. Here, all labels are correct except for “N”, which is mislabeled as “M”.

    Article Snippet: Letters can be recognized with 89% accuracy using the MATLAB built in optical character recognition function, and an average of 81% of points can be accurately labeled and localized.

    Techniques:

    Examples of blue color component image patches that were fed into the optical character recognition function and mislabeled. The output label is displayed in magenta. The fiducial location, as determined by the brightest pixel in the red color channel (not shown), is indicated with a cyan and magenta asterisk.

    Journal: Proceedings of SPIE--the International Society for Optical Engineering

    Article Title: Textual fiducial detection in breast conserving surgery for a near-real time image guidance system

    doi: 10.1117/12.2550662

    Figure Lengend Snippet: Examples of blue color component image patches that were fed into the optical character recognition function and mislabeled. The output label is displayed in magenta. The fiducial location, as determined by the brightest pixel in the red color channel (not shown), is indicated with a cyan and magenta asterisk.

    Article Snippet: Letters can be recognized with 89% accuracy using the MATLAB built in optical character recognition function, and an average of 81% of points can be accurately labeled and localized.

    Techniques: