Recognition of Double Sided Amharic Braille Documents

Abstract

Amharic Braille image recognition into a print text is not an easy task because Amharic language has large number of characters requiring corresponding representations in the Braille system. In this paper, we propose a system for recognition of double sided Amharic Braille documents which needs identification of recto, verso and overlapping dots. We use direction field tensor for preprocessing and segmentation of dots from the background. Gradient field is used to identify a dot as recto or verso dots. Overlapping dots are identified using Braille dot attributes (centroid and area). After identification, the dots are grouped into recto and verso pages. Then, we design Braille cell encoding and Braille code translation algorithms to encode dots into a Braille code and Braille codes into a print text, respectively. With the purpose of using the same Braille cell encoding and Braille code translation algorithm, recto page is mirrored about a vertical symmetric line. Moreover, we use the concept of reflection to reverse wrongly scanned Braille documents automatically. The performance of the system is evaluated and we achieve an average dot identification accuracy of 99.3% and translation accuracy of 95.6%.