Ocr Software Optical Character Recognition Or Optical Crud Recognition

Ocr Software Optical Character Recognition Or Optical Crud Recognition



OCR Software-- Optical Character Recognition or​ Optical Crud Recognition?
Optical Character Recognition (OCR) refers to​ a​ software technology and processes that involve the​ translation of​ printed text into computer searchable text .​
Done correctly,​ OCR enables users to​ search for and retrieve individual words contained within a​ file or​ page .​
In addition,​ when a​ set of​ files is​ indexed,​ users are able to​ search for keywords across an​ entire document library and retrieve each page with exact precision .​
OCR enables users to​ execute searches in​ seconds,​ searches that once could take several hours or​ days to​ complete .​
However,​ this technology did not work well on​ older or​ poor quality documents that contained mixed fonts or​ combinations of​ texts and graphics .​
Until now!!
Due to​ several recent technology advances,​ it​ is​ now possible to​ obtain six-sigma level character accuracy from these types of​ document collections.
Although it​ is​ important to​ keep in​ mind that the​ quality and condition of​ the​ paper documents are still key factors in​ the​ successful OCR conversion,​ dramatically improved results can be obtained by enhancing the​ quality of​ the​ scanned image prior to​ processing.
Noise removal of​ borders,​ speckles and skews are now common on​ the​ more advanced document scanners .​
Furthermore,​ advanced color filter technologies may be used to​ reduce any page background colors,​ in​ conjunction with multi-light image capture technologies to​ remove any shadows cast by page creases that could impact image quality or​ recognition accuracy .​
Once document scanning and processing are complete,​ an​ OCR text layer can actually be added and hidden behind each image .​
An additional orientation filter can be used to​ ensure that the​ best image is​ presented to​ the​ OCR engines .​
To achieve the​ highest conversion accuracy possible,​ the​ characters in​ the​ image can be processed using multi-engine OCR voting technologies that rank each character to​ determine the​ best text recognition fit .​
Then once a​ word is​ generated,​ it​ will be filtered through a​ proprietary lexicon to​ ensure the​ highest quality results .​
Finally,​ this text can be processed utilizing sophisticated layout retention technologies to​ represent the​ image text layout,​ to​ provide the​ best possible text representation for precise search and retrieval .​
After all,​ isn’t that why they call it​ Optical Character Recognition?




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