OCR and ICR Overview

The overwhelming volume of paper-based data outstrips the ability of corporations and government entities to manage documents and records. Computers – working faster and more efficiently than human operators – now perform many of the tasks required for efficient document and content management. Computers best manage two distinct types of documents: electronic documents or data files created originally on a computer and paper documents scanned and recognized as images.

Computers understand alphanumeric characters as ASCII code typed on a keyboard where each character or letter represents a recognizable code. However, computers cannot discern characters and words that are scanned images of paper documents. Therefore, where alphanumeric information must be retrieved from images such as commercial or government applications, credit card applications, tax returns or passport applications, characters (or objects) must first be converted to their ASCII equivalents before they can be recognized as readable text. Translating characters and words contained in images is achieved by three key technologies: 1) OCR (Optical Character Recognition), where characters are converted from machine print to ASCII text, 2) ICR (Intelligent Character Recognition) where human handprint is converted to ASCII text, and 3) Intelligent Recognition, the new generation of technology based on neural networks used to convert handwritten, hand printed or machine-printed data to ASCII text.

OCR & ICR Technology

OCR and ICR technology are analytical artificial intelligence systems that consider only sequences of characters rather than whole words or phrases and do not cross-validate data during the recognition process. Based on the analyses of sequential lines and curves, OCR and ICR make 'best guesses' at characters using database look-up tables to closely associate or match the strings of characters that form words. For these systems to effectively recognize hand printed or machine printed forms, words must be separated into individual characters. That is why most typical administrative forms require people to either hand print into neatly spaced boxes or use combs (tick marks) at the bottom of input lines to force spaces between letters entered on a form. Without the use of combs or boxes, conventional technologies reject fields if people do not follow the structure when filling out forms, resulting in significant administrative overhead and costs to forms processing organizations.

In summary:

OCR technology recognizes only machine print and rejects inputs that contain non-machine print characters. Though most advanced systems are able to recognize multiple fonts (some systems even claim to read any font), they deal only with standard fonts found in mainstream applications, such as Times Roman and Arial. Ultimately, human handwriting is too diverse and unstructured to be recognized by OCR systems.

ICR technology recognizes machine print and handprint. However, it rejects any letter shapes formed as cursive script.

Intelligent Recognition technology

Unlike ICR and OCR systems, Intelligent Recognition technology combines engines that can read words character by character with engines that read whole words or phrases. Therefore, Intelligent Recognition can recognize cursive handwriting, hand print and machine print -- individually or in any combination. Another important distinction of Intelligent Recognition is that it does not require the use of constraining boxes or combs. Accuracy and recognition speed is further improved by cross-validation of data during the recognition process.