The ImageGear Recognition component provides access to document recognition technology.

This core software module provides recognition for almost any document, including those produced on typewriters, dot-matrix printers, ink-jet printers, laser printers, and phototypesetters, as well as photocopied and faxed versions of any document.

Using the ImageGear Recognition component, you can recognize a document image and export the text in one of the supported output formats. These formats include 8-bit ASII and 16-bit Unicode text, Microsoft Word, HTML, and others.

The ImageGear Recognition Component also allows a user to:

• Manage delineated zones of a document page and then specify treatment for those zones. This includes the ability to correct the OCR engine's automatic segmentation between the segmentation phase and the recognition phase.
• Process both text and graphics. The recognition software's ability to distinguish graphics from text can provide the basis of a compound document processing system.
• Automatically detect fax, dot matrix, and other degraded documents and compensate accordingly.
• Recognize Chinese Simplified, Chinese Traditional, Japanese, and Korean languages.

Portions of this document are excerpted from OmniPage Capture SDK 18.6 reference materials. Copyright © 2011 Nuance Communications, Inc. All Rights Reserved. Nuance and the Nuance logo are trademarks or registered trademarks of Nuance Communications, Inc. or its affiliates in the United States and/or other countries.

The figure below illustrates a simple application that takes a page image as input and produces recognized text in a variety of output formats.

This section provides information about the following:

• About the ImageGear Recognition Component
• Working with the ImageGear Recognition Component
• • Migrating from v16 to v17 or later
  • • Data Types
    • Recognition Process and Recognition Data
    • Deleting Objects
    • Formatted Output
    • Training File
    • Output Parameters
    • Error Handling
  • Attaching the Recognition Component to Core ImageGear
  • Error Handling
  • The Recognition Component and Multi-Threading
  • Distributing Recognition Engine Files with Your Application
  • • Distributing Core Recognition Engine Files
    • Distributing Recognition Engine Files for the Western OCR Feature
    • Distributing Recognition Engine Files for the Asian OCR Feature
    • Distributing Recognition Engine Files for the Formatted Output Feature
• Preparing the Image for Recognition
• • Importing Images into the Recognition Component
  • Pre-Processing the Image
  • • Deskewing
    • Despeckling
    • Inversion
    • Resolution Enhancement
    • Rotation and Mirroring
  • Zones and Images
  • • Adding Zones
    • • Auto-Zoning
      • Adding Zones Manually
      • Adding Zones from a Zone File
    • Working with Non-Rectangular Zones
    • Detecting Tables without Visible Cell Separators
• Recognition
• • Recognition Modules
  • Recognition Process
  • Structured Data Output
  • OCR Performance Issues
  • Defining the Character Set
  • Recognized Data Kept in Memory
• Checking
• • Improving Accuracy with the Checking Subsystem
  • • Spell Checking
    • UD Checking
    • User-Written Checking
  • Applying Checking
  • • Applying Spell Checking
    • Applying UD Checking
  • Preparing and Maintaining the User Dictionary
• Output
• • Code Pages
  • Exporting Recognized Data Directly to Text Formats
  • Exporting to a PDF Output Document
  • Exporting to a Formatted Output Document
  • Retaining Format in Final Output Documents
  • Embedded Images in Final Output Documents
  • Confidence Reporting
• Using Highly Compressed PDF
• Using Auto-Redact
• • Using Search
  • • Create an Approximate Regex Object
    • Configure the Search
    • Search for Matches
  • Using Redact
  • • Create the Redactor Object
    • Configure the Redaction
    • Redact Recovered Matches
  • Tips and Tricks
  • • Reacting to Zero Matches
  • Regular Expressions
  • • Basic Patterns (Literals)
    • Sub-Matches
    • Repetition Operators
    • Character Classes
    • • Square Bracket Character Classes
      • Backslash Character Classes
    • More Examples
• Support for Asian Languages
• • Application Areas
  • Conditions
  • Deskew and Orientation
  • Character Attributes
  • Confidence Data and Choices
• Miscellaneous
• • Progress Indication
  • Processing Statistics

The code example below demonstrates loading and recognizing the TEST1.TIF image file. The image contains English, machine-printed text. The result will be saved in the TEST1.TXT text file.

#include <windows.h>    // Windows includes
#include "gear.h"       // Include for Accusoft ImageGear
#include "i_rec.h"      // Include for ImageGear Recognition component
//Loading and recognizing the Image.tif image file. The result will be saved in the Image.txt text file.
VOID Using_VeryFirst()
{
    AT_ERRCOUNT nErrCount;
    HIGEAR     hIGear;
    HIG_REC_IMAGE    hImg;
    nErrCount = IG_comm_comp_attach("REC");
    nErrCount = IG_REC_initialize();
    nErrCount = IG_load_file("Image.tif", &hIGear );
    nErrCount = IG_REC_image_import(hIGear, &hImg);
    nErrCount = IG_image_delete(hIGear);
    nErrCount = IG_REC_output_codepage_set("Windows ANSI");
    nErrCount = IG_REC_output_text_format_set(IG_REC_DTXT_TXTS);
    nErrCount = IG_REC_image_recognize(hImg);
    nErrCount = IG_REC_output_direct_text_write(&hImg, 1, "Image.txt");
    nErrCount = IG_REC_image_delete(hImg);
    nErrCount = IG_REC_close();
}

©2015. Accusoft Corporation. All Rights Reserved.