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This paper presents the first Pashto text image database for scientific research and thereby the first dataset with complete handwritten and printed text line images which ultimately covers all alphabets of Arabic and Persian languages. Language like Pashto, written in a complex way by calligraphers, still requires a mature Optical Character Recognition (OCR), system. Although 50 million people use...
Optical Character Recognition (OCR) of cursive scripts like Pashto and Urdu is difficult due the presence of complex ligatures and connected writing styles. In this paper, we evaluate and compare different approaches for the recognition of such complex ligatures. The approaches include Hidden Markov Model (HMM), Long Short Term Memory (LSTM) network and Scale Invariant Feature Transform (SIFT). Current...
Atomic segmentation of cursive scripts into constituent characters is one of the most challenging problems in pattern recognition. To avoid segmentation in cursive script, concrete shapes are considered as recognizable units. Therefore, the objective of this work is to find out the alternate recognizable units in Pashto cursive script. These alternatives are ligatures and primary ligatures. However,...
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