Short answer question examination using an automatic off-line handwritting recognition system and the Modified Direction Feature

There are no files associated with this record.

Title Short answer question examination using an automatic off-line handwritting recognition system and the Modified Direction Feature
Author Suwanwiwat, Hemmaphan; Blumenstein, Michael Myer
Publication Title Proceedings. ICMV 2010. 2010 The 3rd International Conference on Machine Vision
Editor Juan E. Guerrero
Year Published 2010
Place of publication Chengdu, China
Publisher IEEE
Abstract Handwriting Recognition is one of the most intensive areas of study in the field of pattern recognition. The automatic assessment of exam scripts [1] can benefit from off-line handwriting analysis methods. Off-line automatic assessment systems can be an aid for teachers in the marking process; it reduces the time consumed by the human marker. Recently developed systems in this area have achieved an encouraging assessment yield range executed under constrained conditions. There has not been any recent work in the development of off-line automatic assessment systems using handwriting recognition, even though such systems will clearly benefit the education sector. There is a significant relationship between feature extraction and the recognition response yield; therefore the current research proposes the use of the Modified Direction Feature (MDF) extraction technique [2] and neural networks to develop an automatic assessment system for marking short answer questions. The system has high assessment accuracy (up to 92.31% for hand printed and 91.67% for cursive handwritten). The proposed system also includes marking criteria to augment its accuracy.
Peer Reviewed Yes
Published Yes
Publisher URI
Copyright Statement Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 978-1-4244-8888-9
Conference name 2010 3rd International Conference on Machine Vision (ICMV 2010)
Location Hong Kong
Date From 2010-12-28
Date To 2010-12-30
Date Accessioned 2011-03-13
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Neural, Evolutionary and Fuzzy Computation; Pattern Recognition and Data Mining
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

Show simple item record

Griffith University copyright notice