Bhoi S.Dogra D.P.Roy P.P.2025-02-1720163http://dx.doi.org/10.1109/NCVPRIPG.2015.7490014https://idr.iitbbs.ac.in/handle/2008/1039This paper presents a system for unconstrained handwritten Odia text recognition using Hidden Markov Model (HMM) framework. Existing literature for Odia text recognition works primarily with individual isolated characters. In this study we introduce a Odia dataset of word samples collected from different professionals. Concavity feature from each word image is extracted in our approach. Next, the features are fed to HMM-based sequential classifier for recognition. The experiment has been performed on a large dataset consisting of 4000 words and results obtained are encouraging. � 2015 IEEE.enConference Paper