Title: Database corpus for Yoruba handwriting

Authors: Jumoke Falilat Ajao; Stephen Olatunde Olabiyisi; Elijah Olusayo Omidiora; Oladotun Olusola Okediran; Odetunji Ode Odejobi

Addresses: Department of Computer Science, Kwara State University, Malete, Nigeria ' Department of Computer Engineering and Technology, Ladoke Akintola University, Ogbomoso, Nigeria ' Department of Computer Engineering and Technology, Ladoke Akintola University, Ogbomoso, Nigeria ' Department of Computer Engineering and Technology, Ladoke Akintola University, Ogbomoso, Nigeria ' Department of Computer Engineering, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

Abstract: Non-availability of Yoruba handwritten database has been a major challenge affecting the validation of the Yoruba handwritten recognition system. This paper presents an offline Yoruba handwritten database corpus for validating Yoruba handwritten word recognition system (YHWR). In this research work, 50 medical pathology words were gotten from medical pathology dictionary. The medical pathology words were translated to their Yoruba equivalence and the translated words were hand written by 200 indigenous literate writers with appropriate diacritic signs. The offline handwritten data were scanned using 300 dpi. The database corpus created; converted the scanned images to different image format, different resolutions and different image sizes, to test the effect of different resolutions, different format and image sizes on Yoruba handwritten recognition system. The digitised images were used to create Yourba handwritten database, which, could be used to validate the handwritten recognition system. The database created is considered a raw data that require some level of preprocessing before it can be used for validating the YHWR system.

Keywords: Yoruba; handwriting; corpus; medical pathology and database.

DOI: 10.1504/IJAPR.2018.097102

International Journal of Applied Pattern Recognition, 2018 Vol.5 No.4, pp.270 - 279

Received: 26 Jan 2018
Accepted: 12 Jul 2018
Published online: 20 Dec 2018 *

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