Institute of Information Theories and Applications FOI ITHEA
Abstract:
In this paper, a novel approach for character recognition has been presented with the help of genetic
operators which have evolved from biological genetics and help us to achieve highly accurate results. A genetic
algorithm approach has been described in which the biological haploid chromosomes have been implemented
using a single row bit pattern of 315 values which have been operated upon by various genetic operators. A set of
characters are taken as an initial population from which various new generations of characters are generated with
the help of selection, crossover and mutation. Variations of population of characters are evolved from which the
fittest solution is found by subjecting the various populations to a new fitness function developed. The
methodology works and reduces the dissimilarity coefficient found by the fitness function between the character
to be recognized and members of the populations and on reaching threshold limit of the error found from
dissimilarity, it recognizes the character. As the new population is being generated from the older population,
traits are passed on from one generation to another. We present a methodology with the help of which we are
able to achieve highly efficient character recognition.
