Input Space Transformations for Multi-Classifier Systems based on n-tuple Classifiers with Application to Handwriting Recognition

Sirlantzis, Konstantinos and Hoque, Sanaul and Fairhurst, Michael (2003) Input Space Transformations for Multi-Classifier Systems based on n-tuple Classifiers with Application to Handwriting Recognition. Multiple Classifier Systems (Fourth International Workshop, MCS 2003), Guildford, UK [Lecture Notes in Computer Science LNCS-2709], 2709 . pp. 356-365. ISSN 0302-9743 . (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not available from this repository. (Contact us about this Publication)


In this paper we investigate the properties of novel systems for handwritten character recognition which are based on input space transformations to exploit the advantages of multiple classifier structures, These systems provide an effective solution to the problem of utilising the power of n-tuple based classifiers while, simultaneously, addressing successfully the issues of the trade-off between the memory requirements and the accuracy achieved. Utilizing the flexibility offered by multi-classifier schemes we can subsequently exploit this complementarity of different transformations of the original feature space while at the same time decompose it to simpler input spaces, thus reducing the resources requirements of the sn-tuple classifiers used. Our analysis of the observed behaviour based on Mutual Information estimators between. the original and the transformed input spaces showed a direct correspondence of the values of this information measure and the accuracy obtained. This suggests Mutual Information as a useful tool for the analysis and design of multi-classifier systems. The paper concludes with a number of comparisons with results on the same data set achieved by a diverse set of classifiers. Our findings clearly demonstrate the significant gains that can be obtained, simultaneously in performance and memory space reduction, by the proposed systems.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications), > TK7880 Applications of electronics (inc industrial & domestic) > TK7885 Computer engineering
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Yiqing Liang
Date Deposited: 15 Sep 2008 11:30
Last Modified: 19 May 2014 10:53
Resource URI: (The current URI for this page, for reference purposes)
  • Depositors only (login required):