Logical Structure Analysis for Form Images with Arbitrary Layout by Belief Propagation

Abstract

A new method for analyzing the specific logical structure of forms with unknown layout is proposed. This method uses both the target form image and a generic logical structure as inputs, and models two types of relationships probabilistically: that between strings and logical components, and that between neighboring strings having different logical components. This modeling approach allows strings to be assigned to logical components softly but robustly, and allows the use of an intuitive Bayesian probability network similar to the generic logical structure. Based on this probability network model, strings corresponding to logical components can be determined by belief propagation. This method is demonstrated to be effective by conducting tests on three types of forms.