Optical Character Recognition of Amharic Documents

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Optical Character Recognition of Amharic Documents

In Africa around 2,500 languages are spoken. Some of these languages have their own indigenous scripts. Accordingly, there is a bulk of printed documents available in libraries, information centers, museums and offices. Digitization of these documents enables to harness already available information technologies to local information needs and developments. This paper presents an Optical Charact...

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Integrating Optical Character Recognition and Machine Translation of Historical Documents

Machine Translation (MT) plays a critical role in expanding capacity in the translation industry. However, many valuable documents, including digital documents, are encoded in non-accessible formats for machine processing (e.g., Historical or Legal documents). Such documents must be passed through a process of Optical Character Recognition (OCR) to render the text suitable for MT. No matter how...

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Amharic Character Recognition using a Fast Signature Based Algorithm

The Amharic language is the principal language of over 20 million people mainly in Ethiopia. An extensive literature survey reveals no journal or conference papers on Amharic character recognition. The Amharic script has 33 basic characters each with seven orders giving 231 distinct characters, not including numbers and punctuation symbols. The characters are cursive but not connected and unlik...

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Optical Character Recognition

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Optical Character Recognition Systems

Abstract Optical character recognition (OCR) is process of classification of optical patterns contained in a digital image. The character recognition is achieved through segmentation, feature extraction and classification. This chapter presents the basic ideas of OCR needed for a better understanding of the book. The chapter starts with a brief background and history of OCR systems. Then the di...

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ژورنال

عنوان ژورنال: African Journal of Information & Communication Technology

سال: 2007

ISSN: 1449-2679

DOI: 10.5130/ajict.v3i2.543