Sharp MX-7000N Manual page 45

Scan
Scan Data Capture Accuracy
One of the fastest growing needs for high-speed scanning
is the conversion of legacy hard copy documents into an
electronic format for better information sharing, reduced
storage space, and easier search and data retrieval.
A scan converts a page into an image that is not very
manageable. Most companies use optical character recognition (OCR)
software to convert the images into editable text, which can then be
searched, changed, or incorporated into a new document as required.
The OCR engine recognizes individual images on the page, converting
them into letters, numbers, and other symbols. The OCR engine then runs
complex analysis on the text in conjunction with spell checkers, technical
dictionaries, and other data sources before offering up its best conversion
into electronic format.
This stage can be very time-consuming, especially if the quality of the
scanned data is poor leading to character recognition errors.
To look into this important workflow issue, BERTL ran a series of stan-
dard test patterns with multiple font types, sizes, and colours capturing the
data at various resolutions using both text and text/photo settings. Text is
the default setting for most OCR work due to its 2-bit format, which tends to
produce the best text reproduction.
However, as more documents incorporate images and colour elements,
text/photo, which operates in 8-bit and reproduces gray shades for better
reproduction of images and coloured text elements, is also being used.
After scanning each page of its test originals, BERTL analysts then ran
the scanned files through ABBYY FineReader 8.0, in default configuration.
The impact of the accuracy of the scanning process at the various resolu-
tions and settings is reflected in the number of manual confirmations that
the OCR application demands before the document is deemed clean and
ready to use.
The higher the human intervention rate, the higher the cost of carrying
out the action. As expected, the greatest difficulty in OCR recognition is
found on the smallest 4 point text sections of the test documents.
The choice of OCR application will also have a dramatic effect on the
level of human intervention that is required after the initial scanning has
taken place. For that reason, we have standardized on ABBYY, a well-re-
spected leading OCR software developer.
Our tests are run using the latest level of ABBYY's FineReader 8.0
software in default modes. Through fine tuning of the rich feature set in
ABBYY, an additional portion of the manual intervention could be removed.
However, to maintain benchmark comparison procedures, default settings
were selected.
Copyright © 2006 MCA Internet, LLC dba BERTL. All Rights Reserved. The license under which this document is made available and applicable law prohibit any reproduction or further transmission of any
E x c e p t i o n a l
portion of this document. This document may only be viewed electronically through the www.BERTL.com Web site and may not be stored in electronic or hard copy format. Any reproduction of trademarks is
strictly prohibited. BERTL accepts no responsibility for any inaccuracies or omissions contained in this document.
Office
Sharp MX-7000N
page 45 • September 1, 006
Above is a portion of BERTL's OCR test chart
scanned at 200 dpi (top), 300 dpi (middle) and
600 dpi (bottom) in text format and saved as a
PDF file. The image has been zoomed to 400
percent in Adobe Acrobat and screen-captured
for display.
The top line is 4 point, the middle line is 6
point, and the bottom line 8 point.
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