ICR Technology

Best performing ICR

Intelligent Character Recognition (ICR) converts hand printed characters to their machine print (ASCII) equivalents, representing a significant step forward in technology when compared to older OCR systems that only read machine print. The ability to recognize handprint significantly broadens the range of applications that benefit from automated ICR solutions, saving time and increasing accuracy to levels not attainable by OCR or human intervention.

ICR software is based on the science of neural networks that behave like the human brain when processing information. Because ICR can handle variations in character shape, the term 'intelligent' is combined with 'character recognition' to describe handprint recognition. 

Principles of ICR Technology

Hand printed characters are created by humans, so understanding and interpreting the patterns of human writing is far more complicated than converting simple machine print, because no two people ever write identical characters. Factors such as mood, environment, or stress all conspire to create variations in character writing, causing individuals to form characters differently each time they write or fill out a form. Variations will even appear within the same word, depending on where a character appears. Also, keep in mind that hand printed characters are never evenly spaced across the page, making it difficult for recognition systems to reliably segment words into their component characters.

Like OCR engines, ICR engines execute recognition character-by-character and start by segmenting words into their component characters. Because ICR technology recognizes separate words or word combinations, such as form fields, letters cannot be written sloppily or stuck together.

People read text by scanning entire words, not individual characters. When a person is not clear about, say, whether a character is a 'U' or a 'V', he or she makes a decision based on context rather than the shape of the character. ICR systems (like the most advanced OCR systems) try to imitate this human approach. They use dictionaries that contain possible field values, facilitating word recognition by combining primary recognition results with alternate choices, and then analyzing available alternatives. While ICR is more robust than OCR in handling human printing, as with OCR engines, dictionaries are employed after the recognition process, not during it. Therefore, if a correct guess was not generated during the character segmentation and recognition process, validation with vocabulary lists does not improve the result. Clearly, business and industry is ready for the next leap in recognition technology that addresses the problems inherent in OCR and ICR technologies. 

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.