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STATISTICAL FEATURES EXTRACTION FOR CHARACTER RECOGNITION USING RECURRENT NEURAL NETWORK.

Authors :
Naz, Saeeda
Umar, Arif I.
Ahmed, Saad B.
Ahmad, Riaz
Shirazi, Syed H.
Razzak, Muhammad I.
Zaman, Amir
Source :
Pakistan Journal of Statistics. Jan2018, Vol. 34 Issue 1, p47-53. 7p.
Publication Year :
2018

Abstract

Recent studies show that recurrent neural network provided promising results for character recognition. We have extracted number of features using sliding window approach from normalized Urdu Nasta'liq text line image. The text line is scanned from right to left and top to bottom by considering Urdu script properties and extracted geometrical or statistical features, zoning and raw pixels features. We conduct four studies like sliding window with non-overlapped frame, sliding window with overlapped area with previous frame, multiple zones in a frame and raw pixels. In this paper, we evaluated MDSLTM with CTC output layer on UPTI dataset for Urdu character recognition. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10129367
Volume :
34
Issue :
1
Database :
Academic Search Index
Journal :
Pakistan Journal of Statistics
Publication Type :
Academic Journal
Accession number :
127364555