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Frequently Asked Questions About OCR

What is OCR software? 
OCR, or optical character recognition, is software that finds and identifies all characters (numbers, letters, punctuation, etc.) in an image, pdf or other document. 

Which OCR technology is the best? 
There are many good OCR engines available. The best results, however, come from systems that use a voting engine” to combine several OCR engines/technologies.  

How can I improve my OCR accuracy? 
Effective pre-processing can greatly improve OCR results. Additionally, computer vision technology can use “context clues” to further increase accuracy. 

Can OCR detect lines, shapes, colors, or other features on page? 
No, even advanced OCR engines only retrieve text. To detect other features, you need a more comprehensive data capture software. 

Does OCR include document layout analysis? 
No, document layout analysis requires computer vision technology which is beyond the abilities of a basic OCR engine. A few of the more advanced OCR vendors have begun incorporating document layout analysis to help arrange text correctly within a page to understand tables and spreadsheets. 

Does OCR read handwriting? 
A few OCR engines claim to extract handwriting but their recognition rates are far lower than for printed text, and not nearly accurate enough to incorporate into a broader automation solution. Our data capture software, however, can identify and classify handwritten documents by type, even though it cannot extract the exact content. 

Does OCR work for any language? 
OCR engines can be programmed to recognize almost any language. Once running, however, they can only recognize the specific language which they were set up. A single machine can sometimes be set up to recognize two or three similar languages, but the more languages a machine is supposed to recognize, the lower its accuracy will be. 

What is the difference between OCR and OMR? 
OCR identifies specific characters. OMR, or optical mark recognition, recognizes marks on a document but does not try to identify those marks. OMR might be used, for example, to detect whether box or bubble on a multiple-choice exam or survey is filled in. 

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