A lot of the documents we encounter require there to be a signature. In data capture, these documents add an additional complexity as an operator either before data capture or after has to make sure each document is signed. When a document is not signed it very often has to go a different path of approvals. Often organizations will ask OCR vendors to read the signature in a form. Ability to recognize signatures is very expensive and requires a database of pre-existing signatures so often not feasible. But ability to find a signature and confirm it’s presence is not that difficult at all.
Because documents with a signature line almost always have to be checked to assure a signature is there. This is an additional step of processing. However, companies often don’t realize that the data capture software they are using can get all the fields off of the document and check accurately if a signature is present. By doing so they remove any additional steps and can flag only the documents that are not reporting a signature.
Using OMR, optical mark recognition technology, you can determine if a signature is present. In its simplest form, OMR check’s to see if there is a substantial amount of black pixels in a white space. At a certain threshold of black, that field will be considered checked. If in a data capture setup you put an OMR field in the location where a signature should be then you will know that if it reports checked, there is signature present, and if unchecked, there likely is no signature.
Although you are not reading the signature, OMR is a fast and accurate way to see if signatures are present and avoid the additional manual step of checking for signed documents.
Ilya Evdokimov is a long-term practitioner and expert in leading Optical Character Recognition (OCR), Data Capture and Document Processing techniques, technologies and solutions. With over 15 years of experience spanning enterprise software implementations, mobile applications development, cloud-based systems integration and desktop-level automation, Ilya Evdokimov uses through industry knowledge and experience to achieve high efficiency and workflow optimization in most challenging paper-dependent and digital image capture environments.