OCR and Other Recognition Technologies

Optical Character Recognition (OCR)

OCR technology – printed text recognition is available for 202 languages, including:

 See The Full List of Supported Languages


Intelligent Character Recognition (ICR)


Optical Mark Recognition (OMR)

The ABBYY’s OMR technology recognizes simple checkmarks, grouped checkmarks, model checkmarks and checkmarks with “corrections” made by hand in different variations:

OMR delivers accuracy rate of 99.995%.


Optical Barcode Recognition (OBR)


Recognition modes

With the Engine's pre-defined processing modes, developers have the ability to quickly set up and tune the processing speed and accuracy in a way which is the most appropriate for their needs. In addition to the default processing mode, both OCR and ICR recognition can be performed in normal, fast and balanced recognition modes:

The most accurate mode for achieving the highest quality of recognition. This mode is highly recommended if you are planning to reuse recognized content and in other tasks when the accuracy is the critically important issue.

Designed for high-volume document processing and for the cases when speed is of primary importance. This mode increases processing speed by 200-250% making the technology ideal for use in content management (CMS), document management (DMS) and archiving systems.

Sets the intermediate values of recognition accuracy and speed between Normal and Fast modes. Generally it provides higher speed for almost the same accuracy level as Normal mode.

Full Text and Field-Level Recognition

There are two types of recognition that can be separated: full text and field-level recognition. The main difference is that full text recognition usually includes OCR technology and used for document conversion. Field-level recognition includes OCR, ICR and other technologies that are used in local area for recognizing and extraction particular data.

The following table shows specifications of these recognition types: 


 Full text recognition

Field-level recognition

Where is used

Document conversion, books archiving

Data capture / Data extraction

Document analysis

General document analysis, document analysis for invoices, document analysis for full-text indexing

Manual blocks specification for field-level recognition


OCR with up to 99% accuracy

OCR, ICR, OMR, Barcodes recognition with predefined data types and values range. 99.99% accurate.


Recommended for content reuse

Obligatory in most cases


Used for document retrieval

Not used

Export of recognition results

Document files (RTF, DOC, PDF, etc.)

Export to XML file or database

Full text recognition

Full text recognition is a basic recognition type for different tasks, like:

Learn more about recognition tasks ›

All of them require the recognition (OCR) of whole text on document (page). Before recognition the document analysis usually processes for splitting and correct orientation of pages, detection of text blocks, pictures and other objects.

Then after OCR, document synthesis rebuilds the structure and layout of document (for content reuse task) or just retrieves the correct text order for complex documents with several text columns and pictures (for archive scenario). Resulting text is exported depending on task as pure text or as a document of supported format.

The text could be manually verified to increase accuracy, especially for future reuse.


Field-level recognition

ABBYY FineReader Engine 11 delivers complete field-level recognition capabilities to support key business processes such as forms processing, keyword classification, and keyword indexing. Powerful image processing functions increase its ability to intelligently detect small zone areas of any quality, with any type of graphic specifics that may affect recognition accuracy (i.e. underlined text, after-scanning garbage, spaces in the text, etc.)

Key functionality for field-level or zonal recognition includes multilingual OCR and ICR, OMR, barcode recognition and a range of specific functions, such as:

Field-level recognition is supported by the Engine’s special tools for developers such as Voting API and "On-the-Fly" Recognition Tuning. 


User languages

ABBYY FineReader Engine provides an API for creating and editing recognition languages, creating copies of predefined recognition languages and adjusting them, and adding new words to user languages.

Below are two examples illustrating how user languages can help you to improve recognition quality:


Pattern Training

In the vast majority of cases FineReader Engine can successfully read texts without prior training. However, in cases including recognition of decorative or outlined fonts or bulk input of low print quality documents, preliminary pattern training will prove useful.

The OCR SDK allows you to create and use user patterns or import them from the ABBYY FineReader desktop application (Professional or Corporate Edition). FineReader Engine is flexible and applicable to applications of any architecture - whether a client workstation or server-based solution.

Want to try?

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