An investigation of novel combined features for a handwritten short answer assessment system

Suwanwiwat, Hemmaphan, Pal, Umapada, and Blumenstein, Michael (2016) An investigation of novel combined features for a handwritten short answer assessment system. In: Proceedings of the 15th International Conference on Frontiers in Handwriting Recognition. pp. 102-107. From: ICFHR 2016: 15th International Conference on Frontiers in Handwriting Recognition, 23-26 October 2016, Shenzhen, China.

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Abstract

This paper proposes an off-line automatic assessment system utilising novel combined feature extraction techniques. The proposed feature extraction techniques are 1) the proposed Water Reservoir, Loop, Modified Direction and Gaussian Grid Feature (WRL_MDGGF), 2) the proposed Gravity, Water Reservoir, Loop, Modified Direction and Gaussian Grid Feature (G_WRL_MDGGF). The proposed feature extraction techniques together with their original features and other combined feature extraction techniques were employed in an investigation of the efficiency of feature extraction techniques on an automatic off-line short answer assessment system. The proposed system utilised two classifiers namely, artificial neural networks and Support Vector Machines (SVMs), two type of datasets and two different thresholds in this investigation. Promising recognition rates of 94.85% and 94.88% were obtained when the proposed WRL_MDGGF and G_WRL_MDGGF were employed, respectively, using SVMs.

Item ID: 49469
Item Type: Conference Item (Research - E1)
ISBN: 978-1-5090-0981-7
Research Data: http://ieeexplore.ieee.org/document/7814047/
Date Deposited: 29 Jun 2017 01:48
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460306 Image processing @ 50%
46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460308 Pattern recognition @ 50%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
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