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Factored Convolutional Neural Network for Amharic Character Image Recognition
DFKI-German Research Center for Artificial Intelligence, University of Kaiserslautern, DE, Kaiserslautern, DE.
DFKI-German Research Center for Artificial Intelligence, University of Kaiserslautern, DE, Kaiserslautern, DE.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0003-4029-6574
Bahir Dar Institute of Technology, Ethiopia.
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2019 (English)In: 2019 IEEE International Conference on Image Processing: Proceedings, IEEE, 2019, p. 2906-2910Conference paper, Published paper (Other academic)
Abstract [en]

In this paper we propose a novel CNN based approach for Amharic character image recognition. The proposed method is designed by leveraging the structure of Amharic graphemes. Amharic characters could be decomposed in to a consonant and a vowel. As a result of this consonant-vowel combination structure, Amharic characters lie within a matrix structure called 'Fidel Gebeta'. The rows and columns of 'Fidel Gebeta' correspond to a character's consonant and the vowel components, respectively. The proposed method has a CNN architecture with two classifiers that detect the row/consonant and column/vowel components of a character. The two classifiers share a common feature space before they fork-out at their last layers. The method achieves state-of-the-art result on a synthetically generated dataset. The proposed method achieves 94.97% overall character recognition accuracy.

Place, publisher, year, edition, pages
IEEE, 2019. p. 2906-2910
Series
IEEE International Conference Image Processing, E-ISSN 2381-8549
Keywords [en]
Amharic character image, Factored CNN, Fidel Gebeta, Row-column order, OCR
National Category
Computer Sciences
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-78656DOI: 10.1109/ICIP.2019.8804407ISI: 000521828603005Scopus ID: 2-s2.0-85076799443OAI: oai:DiVA.org:ltu-78656DiVA, id: diva2:1426283
Conference
2019 IEEE International Conference on Image Processing, September 22–25, 2019, Taipei, Taiwan
Note

ISBN för värdpublikation: 978-1-5386-6249-6

Available from: 2020-04-24 Created: 2020-04-24 Last updated: 2020-04-24Bibliographically approved

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Liwicki, Marcus

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