Identification of Very Similar Filled-in Forms with a Reject Option

In this work, a technique addressed to the reliable identification of very similar filled-in forms, with a reject option, is proposed. The method is based on the automatic detection of the most discriminant regions at the image level, to be used by a distance-based classifier. Experiments included multi-page form images and the results suggest that a very high accuracy can be achieved when identifying previously known types of forms, even when unpredictable fill-in data and significant noise from the scanning process appear on the test images. Likewise, it is shown that the probability that an unknown type of document is not rejected is very low. The presented technique could also be applied to other kinds of documents.