Document classification using associative memories

Abstract

Summary form only given. An automated document classification system is presented which deals with documents containing horizontal lines and text. The system consists of two major components: the preprocessing module and the classification module. The preprocessing module digitizes input documents, scales them to a suitable level of resolution, and locates horizontal lines. The classification module is a heteroassociative memory that makes the decision on the type of input documents in the form of multiple line patterns. The experimental results using unidirectional linear associative memory show that the classification error rate is near zero. Discussions about employing the bidirectional associative memory in the classification module is also given.<>