A generic form processing approach for large variant templates

Abstract

In today's world, form processing systems must be able to recognize mutant forms that appear to be based on differing templates but are actually only a variation of the original. A single definition of a representative template actually covers large varieties of the same logical templates. We developed a method and system, similar to the human visual system, which differentiates between templates via features such as logos, dominant words, and geometrical shapes, while ignoring minor details and variations. When the system finds an appropriate template, it then decodes the content of the form. Our approach has been applied in several scenarios with encouraging results. © 2009 IEEE.