Statistical features extraction for character recognition using recurrent neural network
Version 2 2024-06-05, 06:28Version 2 2024-06-05, 06:28
Version 1 2019-11-26, 08:57Version 1 2019-11-26, 08:57
journal contribution
posted on 2024-06-05, 06:28 authored by S Naz, AI Umar, SB Ahmed, R Ahmad, SH Shirazi, Imran RazzakImran Razzak, A Zaman© 2018 Pakistan Journal of Statistics. 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.
History
Journal
Pakistan journal of statisticsVolume
34Pagination
47-53Location
Lahore, PakistanISSN
1012-9367Language
engPublication classification
C1.1 Refereed article in a scholarly journalIssue
1Publisher
PJSPublication URL
Usage metrics
Categories
Licence
Exports
RefWorksRefWorks
BibTeXBibTeX
Ref. managerRef. manager
EndnoteEndnote
DataCiteDataCite
NLMNLM
DCDC