Abstract
A bulk of real-life documents contain vital information and knowledge about history, culture, economy, politics, religion, and science that are written in Ethiopic script. This knowledge has to be shared and the advancement of technology like Optical Character Recognition (OCR) brings the need to digitize documents and make them available for public use. OCR is a process that allows printed, typewritten, and handwritten text to be recognized optically and converted into a machine-readable format that can be accepted by a computer for further processing. Nowadays, effective OCR systems have been developed for languages, like English that has wider use internationally. Researches in the area of Amharic OCR are ongoing since 1997. Attempts were made in adopting recognition algorithms to develop Amharic OCR. This study is, thus, an attempt made to develop an OCR system for real-life documents written in Ethiopic characters. In this study we propose a novel feature extraction schema using Gabor Filter and Principal Component Analysis (PCA), followed by a Genetic Algorithm (GA) based on supported vector machine classifier (SVM). The prototype was tested on real-life Ethiopic documents such as books, newspapers, and magazines, in which an average accuracy of 98.33% for Ethiopic characters is registered.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Marinai, S., et al.: Introduction to document analysis and recognition. IEEE Trans. PAMI 27(1), 23–43 (2006)
Encyclopedia Britannica, Ethiopia: Encyclopaedia Britannica Ultimate Reference Suite. Encyclopaedia Britannica, Chicago (2010)
Meshesha, M., Jawahar, C.V.: Matching word images for content-based retrieval from printed document images. Int. J. Doc. Anal. Recogn. 11(1), 29–38 (2008)
Assabie, Y., et al.: Optical character recognition of Amharic text: an integrated approach (Master thesis). School of Information Studies for Africa, Addis Ababa University, Addis Ababa, Ethiopia (2002)
Belay, B., Habtegebrial, T., Meshesha, M., Liwicki, M., Belay, G., Stricker, D.: Amharic OCR: an end-to-end learning. Appl. Sci. 10(3), 1117 (2020). https://doi.org/10.3390/app10031117
Eikvil, L., et al.: OCR - Optical Character Recognition, pp. 317–326 (December 1993). Norsk Regnesentral, P.B. 114 Blindern, N-0314 Oslo
Getu, S., et al.: Ancient Ethiopic Manuscripts Character Recognition, vol. 38 (July 2020)
Tanner, S., et al.: Deciding whether optical character recognition is feasible. King’s Digital Consultancy Service (December 2004)
Ahmed, M., Abidi, A.: Review on optical character recognition. IRJET 06, 3666–3669 (2019)
Cowell, J., Hussain, F.: Amharic character recognition using a fast signature based algorithm. In: Proceedings of the 7th International Conference on Information Visualization, pp. 384–389 (2003)
Belay, B., Habtegebrial, T., Belay, G., Meshesha, M.: Learning by injection : attention embedded recurrent neural network for Amharic text-image recognition (October 2020)
Alemu, W., et al.: The application of OCR techniques to the Amharic script (Master thesis). School of Information Studies for Africa, Addis Ababa University, Addis Ababa, Ethiopia (1997)
Demilew, F.A., Sekeroglu, B.: Ancient Geez script recognition using deep learning. SN Appl. Sci. 1(11), 1–7 (2019). https://doi.org/10.1007/s42452-019-1340-4
Abebe, E., et al.: Recognition of formatted Amharic text using optical character recognition (Master thesis). School of Information Studies for Africa, Addis Ababa University, Addis Ababa, Ethiopia (1998)
Teferi, D., et al.: Optical character recognition of typewritten Amharic text (Master thesis). School of Information Studies for Africa, Addis Ababa University, Addis Ababa, Ethiopia (1999)
Meshesha, M.: A generalized approach to optical character recognition of Amharic texts (Master thesis). School of Information studies for Africa, Addis Ababa University, Addis Ababa, Ethiopia (2000)
Taddesse, N., et al.: Handwritten Amharic text recognition applied to the processing of bank cheques (Master thesis). School of Information Studies for Africa, Addis Ababa University, Addis Ababa, Ethiopia (2000)
Meshesha, M., Jawahar, C.: Optical character recognition of Amharic documents. Afr. J. Inf. Commun. Technol. 3(2) (2007)
Yaregal, A., Josef, B.: HMM-based handwritten Amharic word recognition with feature concatenation. In: Proceedings of the International Conference on Document Analysis and Recognition, Barcelona, Spain, 26–29 July 2009, pp. 961–965 (2009)
Trier, O.D., Jain, A.K.: Goal-directed evaluation of binarization methods. IEEE Trans. Pattern Anal. Mach. Intel. 17(12), 1191–1201 (1995). https://doi.org/10.1109/34.476511
Asnake, B., et al.: Retrieval from real-life Amharic document images (Master Thesis). School of Information Science, Addis Ababa University, Addis Ababa, Ethiopia (June 2012)
Meshesha, M., et al.: Recognition and retrieval from document image collections. Ph.D. Dissertation, International Institute of Information Technology, India (2008)
Mori, M., et al.: Character Recognition. Sciyo (2010). ISBN 978-953-307-105-3
Asht, S., Dass, R.: Pattern recognition techniques: a review. Int. J. Comput. Sci. Telecommun. 3(8), 25–29 (2012)
Zhang, D., Lu, G.: A comparative study on shape retrieval using Fourier descriptors with different shape signatures. In: Proceedings of the IEEE International Conference on Multimedia and Expo, Tokyo, Japan, pp. 1139–1142 (2001)
Haghighi, M., et al.: Identification using encrypted biometrics. Department of Electrical and Computer Engineering, University of Miami, pp. 440-448 (2013)
Akram, S., Dar, M.-U.-D., Quyoum, A.: Document image processing - a review. Int. J. Comput. Appl. 10(5), 35–40 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Gebremichael, H.T., Mengistu, T.M., Beyene, M.M., Mengistu, F.G. (2022). OCR System for the Recognition of Ethiopic Real-Life Documents. In: Berihun, M.L. (eds) Advances of Science and Technology. ICAST 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 411. Springer, Cham. https://doi.org/10.1007/978-3-030-93709-6_38
Download citation
DOI: https://doi.org/10.1007/978-3-030-93709-6_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-93708-9
Online ISBN: 978-3-030-93709-6
eBook Packages: Computer ScienceComputer Science (R0)