Handwritten Mail Classification Experiments with the Rimes Database

Abstract

In this paper, we consider the task of automatic handwritten mail classification and we investigate the relation between the transcription rate and the classification rate. Several configurations of a multi-word handwriting recognizer using different language models are tested and their word recognition rates on the documents to be classified are reported. For the document classification task, we have investigated three different classifiers (KNN, SVM, AdaBoost). All the experiments were conducted on the public database Rimes.