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Authors: Fuma Horie 1 and Hideaki Goto 2

Affiliations: 1 Graduate School of Information Sciences, Tohoku University, Sendai and Japan ; 2 Cyberscience Center, Tohoku University, Sendai and Japan

Keyword(s): Random Image Feature, Japanese Scene Character Recognition, Synthetic Scene Character Data, Ensemble Voting Classifier, Multi-Layer Perceptron.

Related Ontology Subjects/Areas/Topics: Ensemble Methods ; Feature Selection and Extraction ; Pattern Recognition ; Theory and Methods

Abstract: Scene character recognition is challenging and difficult owing to various environmental factors at image capturing and complex design of characters. Japanese character recognition requires a large number of scene character images for training since thousands of character classes exist in the language. In order to enhance the Japanese scene character recognition, we utilized a data augmentation method and an ensemble scheme in our previous work. In this paper, Random Image Feature (RI-Feature) method is newly proposed for improving the ensemble learning. Experimental results show that the accuracy has been improved from 65.57% to 78.50% by adding the RI-Feature method to the ensemble learning. It is also shown that HOG feature outperforms CNN in the Japanese scene character recognition.

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Paper citation in several formats:
Horie, F. and Goto, H. (2019). Japanese Scene Character Recognition using Random Image Feature and Ensemble Scheme. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 414-420. DOI: 10.5220/0007341904140420

@conference{icpram19,
author={Fuma Horie. and Hideaki Goto.},
title={Japanese Scene Character Recognition using Random Image Feature and Ensemble Scheme},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2019},
pages={414-420},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007341904140420},
isbn={978-989-758-351-3},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Japanese Scene Character Recognition using Random Image Feature and Ensemble Scheme
SN - 978-989-758-351-3
IS - 2184-4313
AU - Horie, F.
AU - Goto, H.
PY - 2019
SP - 414
EP - 420
DO - 10.5220/0007341904140420
PB - SciTePress