Exploration of Improved Methodology for Character Image Recognition of Two Popular Indian Scripts using Gabor Feature with Hidden Markov Model
Shubhra Saxena, Vijay Dhaka · International Journal of Computer Applications · 2015
Handwritten character recognition plays an important role in the modern world.It can solve more complex problems and make the human's job easier.The present work portrays a novel approach in recognizing handwritten cursive character using Hidden Markov Model (HMM) .The method exploits the HMM formalism to capture the dynamics of input patterns, by applying a Gabor filter to a character image, observation feature vector is obtained, and used to form feature vectors for recognition.The HMM model is proposed to recognize a character image.All the experiments are conducted by using the Matlab tool kit.