Unmatched Recognition Capabilities

Incorporating a range of recognition functionality via the ScanSoft® OmniPage® Capture SDK, our OCR component is more than just an OCR toolkit. We provide unsurpassed recognition accuracy for almost any document type — barcode, OCR, ICR, and OMR.

Barcode

ImageGear barcode functionality provides an API for reading barcodes in all supported image formats. In imaging, barcodes provide a means of quickly obtaining information for use in indexing data or for use by an application.

The ImageGear barcode support provides the ability to search for a barcode on a page, recognize its symbology and recognize the data within. Images with barcodes can be acquired through scanning or using ImageGear operations to read previously saved scanned images from memory. Highlights include the following:

Selection of symbologies for recognition
Setting barcode properties (i.e., width, height, orientation, image quality, checksum verification, spot-filter use, effort of searching and search order
Setting barcode regions relative to the image's rectangular ROI
Reading barcodes from the region set
Getting distinct barcode text and other information found through a previous reading of barcodes
Removing barcode region and freeing-up memory allocated for the region

Barcode symbologies are either one-dimensional (with all the data encoded in the horizontal dimension) or two-dimensional (with data encoded in the horizontal and vertical dimensions). ImageGear barcode support is available in Basic and Advanced modules. The Basic module provides recognition of the following 1D symbologies:

CODABAR
128
39 (a.k.a. 3 of 9)
EAN 8/13
EAN/UPC with 2 & 5 digit supplement
ITF (2 of 5 interleaved)
PostNet
UCC Code 128
UPC-A
UPC-E 6 digit

OCR - Optical Character Recognition

The ImageGear OCR component enables developers to build recognition applications for Windows systems. When utilized in an application, it will acquire a page image as input and produce recognized text in a variety of output formats.

ImageGear OCR provides a new scalable voting architecture that provides developers with two pre-made voting interfaces along with direct access to three leading OCR engines, enabling the best possible results for their applications:

MOR OCR Engine

Supports 114 languages s
Supports a maximum of 500 zones on one image
Supports Omnifont, Draftdot24 and OCR-A filling methods
Supports character training to achieve improved accuracy
Provides three page-level accuracy and speed trade-off settings (Accurate, Balanced and Fast)
Provides Checking Subsystem-based correction

MTX (Mtext) OCR Engine

The fastest of the selectable OCR engines
Support for 12 languages
Supports a maximum of 64 zones on one image
Supports Omnifont, Draftdot9 and Draftdot24 filling methods
Provides two page-level accuracy and speed trade-off settings (combined Accurate/Balanced and Fast)
Provides Checking Subsystem-based correction

FireWorX OCR Engine

Optimized for speed
Support for 54 languages
Supports a maximum of 2,500 zones on one image
Supports Omnifont filling methods
Supports character training to achieve improved accuracy

ImageGear also offers a significantly enhanced character confidence value reporting system, providing a wide range of confidence values. This offers developers the ability to set thresholds for letter accuracy within their applications.

To further improve output accuracy, quality format retention is available. This separates text, graphics, tables and columns to provide greater fidelity.

ICR - Intelligent Character Recognition

Developers have a choice of integrating two ICR (handprint OCR) recognition modules, including a numbers only module and an alphanumeric handprint recognition module. The numeric-only module is designed for a restricted character set, and can recognize the following: Digits (0-9), Plus sign (+), Minus sign (-), Period or full-stop (.), Comma (,).

Typical recognition time is 280-310 characters-per-second (measured on a computer with 1.5 GHz Pentium processor, 256 MB RAM, running Windows 2000).

The Alphanumeric ICR module recognizes hand-printed characters (both upper- and lower-case) of nearly 100 languages, 15 with dictionary support, including:

Catalan
Czech
Danish
Dutch
English
Finnish
French
German
Hungarian
Italian
Norwegian
Polish
Portuguese
Spanish
Swedish

Typical recognition time is 150-220 characters-per-second (measured on a computer with 1.5 GHz Pentium processor, 256 MB RAM, running Windows 2000).

OMR - Optical Mark Recognition

The OMR recognition module is used for recognizing optical marks. Typical areas of application include questionnaires, educational tests, and in reporting or ordering sheets—where the documents being processed are form-like and filled in by respondents.

The frame can be a rectangle, hexagon, circle or ellipse and can be filled in by any method (x, tick, hatching, horizontal or vertical lines, etc.). The frame may be visible or invisible (scanner dropout) in the image sent for recognition. Recognition accuracy is 99.95 % and the average recognition time is 0.005 seconds per checkbox zone (measured on a computer with 166 MHz Pentium Processor & 16 MB RAM).