A hybrid feature extraction scheme for Off-line English numeral recognition

This paper aims at presenting a rotation invariant feature extraction scheme to support well known result oriented recognizer HMM. Hybrid feature extraction method consists of features due to moment of inertia (FMI) and projection features. Projection features have been applied in case of digits (2 and 3) and for other numerals FMI is introduced. Any recognition system consists of two major components viz. Feature extraction method and recognizer. This paper uses Hidden Markov Model (HMM) as recognizer to recognize Off-line handwritten English numerals due to its inherent specialities and promising results in automatic speech recognition. Our data-base consists of own collected data from people of different ages and CENPARMI data. The percent recognition accuracy of self collected samples and CENPARMI samples have been found to be 91.7% and 91.2% respectively.