Use of structured pattern representations for combining classifiers

Abstract

In Pattern Recognition, there are problems where distinct representations can be obtained for the same pattern, and depending on the type of classifiers (statistical or structural) one type of representation is preferred versus the others. In the last years, different approaches to combining classifiers have been proposed to improve the performance of individual classifiers. However, few works investigated the use of structured pattern representations. In this paper combination of classifiers has been applied using tree pattern representation in combination with strings and vectors for a handwritten character classification task. In order to save computational cost, some proposals based on the use of both embedding structured data and refine and filter framework are provided. © 2008 Springer Berlin Heidelberg.