OCR & Form Recognition

Form recognition is an area very relevant to the document imaging industry. In fact, it is one way for a company to save money by automating processes that are now done manually. It is estimated that industry spends as much as $20 Billion annually on field coding, which means taking information that people have written or typed on form documents, invoices, etc., and keying this information into a database. Certainly, some of this work could be automated - the question is, how much?

There are multiple problems involved in "form recognition". The most straightforward forms recognition to solve is to recognize a "fixed form", where the form always has the exact same appearance. Even in a fixed form environment, where the form type can be detected with almost absolute certainty, there can be problems. Assume the task at hand is to identify the precise form type and then extract certain fields. It's possible that the fields are handwritten, or even if machine printed, that OCR rates are less than 100%. So what needs to be learned is not just the form characteristics, but also the constraints on the different fields to be extracted, e.g., date field. For handwritten documents, ICR is less than reliable so that redundancy can also be a key factor in reliability. If there are multiple fields on the form that give the same, or database related, pieces of information these can be combined to yield a much higher recognition accuracy.

There are forms that are not fixed. Examples can include bank transaction statements that resemble business letters and differ based on issuing bank. There are Dept. of X files on an individual, where X could be Housing, Corrections, Employment, Education, etc. These documents may differ based on State of issue, and within each State, differ by County. The forms again may not be fixed, but may vary in structure. The field information may be embedded somewhere in the document.

Most form recognition problems where companies could potentially see serious ROI with a fully-automated or semi-automated recognition system, are beyond the capabilities of current off-the-shelf OCR, form recognition, and data extraction systems. That does not mean, however, that a solution cannot be engineered to a company's specifications based on a company's unique set of forms to be processed, data to be extracted, possible data redundancy, and other factors. Any system that involves 3 or more full-time data entry personnel, from menial data entry to more complex data entry and analysis is a candidate for automation (or at least semi-automation). Consulting a company with the right expertise in the area of form recognition (e.g., CVISION) can make all the difference.

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