System and method for automatically classifying heterogeneous business

Abstract

Business forms are a special class of documents typically used to collect or distribute data; they represent a vast majority of the paperwork need to conduct business. The present invention provides a pattern recognition system that classifies digitized images of business forms according to a predefined set of templates. The process involves a training phase, during which images of the template forms are scanned, analyzed and stored in a data dictionary, and a recognition phase, during which images of actual forms are compared to the templates in the dictionary to determine their class membership. The invention provides the feature extraction and matching methods, as well as the organization of the form dictionary. The performance of the system was evaluated using a collection of computer generated test forms. The methodology for creating these forms, and the results of the evaluation are also described. Business forms are characterized by the presence of horizontal and vertical lines that delimit the useable space. The present invention identifies these so called regular lines in bi-level digital images to separate text from graphics before applying an optical character recognizer; or as a feature extractor in a form recognition system. The approach differs from existing vectorization, line extraction, and text-graphics separation methods, in that it focuses exclusively on the recognition of horizontal and vertical lines.