Japanese scene character recognition using random image feature and ensemble scheme

Fuma Horie, Hideaki Goto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods
EditorsMaria De Marsico, Gabriella Sanniti di Baja, Ana Fred
PublisherSciTePress
Pages414-420
Number of pages7
ISBN (Electronic)9789897583513
DOIs
Publication statusPublished - 2019
Event8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019 - Prague, Czech Republic
Duration: 2019 Feb 192019 Feb 21

Publication series

NameICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods

Conference

Conference8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019
Country/TerritoryCzech Republic
CityPrague
Period19/2/1919/2/21

Keywords

  • Ensemble Voting Classifier
  • Japanese Scene Character Recognition
  • Multi-Layer Perceptron
  • Random Image Feature
  • Synthetic Scene Character Data

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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