Data verification is performed by comparing recognition results with the image of any document part. When the program is not absolutely certain about the accuracy of recognition of a certain characters, it marks them as recognized "unreliably." The purpose of the verification process is to verify such characters and correct any errors if necessary.

FlexiCapture Engine offers effective and convenient instruments for checking the validity of captured data and tracking recognition errors:

Rules-based  verification

Recognised data can automatically be checked if needed. This covers simple range checking, comparison with a known value (e.g. supplied as a regular expression or taken from a database), and comparison of data items within one document. Finally, scripts can be used to create very sophisticated checking rules.

Rules could be easily managed with a separate tool – FlexiCapture product that is supplied with FlexiCapture Engine to set up Document Definitions. This makes solution manteinance at production stage easier since only Document Definition have to be changed, without touching any line of the code.

Nevertheless if developers prefer the rules to be managed via code this is easile configurable using the product API.

Group verification

Group verification is a verification mode whereby identically recognized characters are submitted for verification in groups. Group verification involves grouping character images recognized as having identical values and displaying them in a verifier screen, enabling the operator to easily identify and correct characters that deviate from the group.


Context verification

Context verification is a verification mode intended for effective correction of errors of "well-recognized" fields, i.e. fields whose range of values is known or can be easily identified. An example of such a field is a field containing a country or city name.



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