Handwritten tibetan character recognition using hidden markov model

Title

Handwritten tibetan character recognition using hidden markov model

Creator

Dhondup N.; Jose D.V.

Description

The Tibetan language which is one of the four oldest and most original languages of Asia is elemental to Tibetan identity, culture and religion and it convey very specific social and cultural behaviors, and ways of thinking. The annihilation of the Tibetan language will have tremendous consequences for the Tibetan culture and hence it is important to preserve it. Tibetan language is mainly used in Tibet, Bhutan, and also in parts of Nepal and India. Tibetan script is devised based on the Devanagari model and Sanskrit based grammars. In this paper, a method for Tibetan handwritten character recognition based on density and distance feature detection is presents. To get a better classification result, images are converted into binary and noise removal is done by using Otzsos method. Features are extracted by normalizing the image based on distance and density of the pixel in the image. Finally, Hidden Markov Model is used for character classification. BEIESP.

Source

International Journal of Recent Technology and Engineering, Vol-8, No. 1, pp. 749-753.

Date

2019-01-01

Publisher

Blue Eyes Intelligence Engineering and Sciences Publication

Subject

Density; Distance; Hidden markov model; Otzso; Tibetan Character

Coverage

Dhondup N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, Karnataka, India; Jose D.V., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, Karnataka, India

Rights

Restricted Access

Relation

ISSN: 22773878

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067894478&partnerID=40&md5=854d24c09175d6b9ed93b5b5775b875c