Recognition is one of the basic characteristics of human brain, and also for the living creatures. It is possible to recognize images, persons, or patterns according to their characteristics. This recognition could be done using eyes or dedicated proposed methods. There are numerous applications for pattern recognition such as recognition of printed or handwritten letters, for example reading post addresses automatically and reading documents or check reading in bank.
One of the challenges which faces researchers in character recognition field is the recognition of digits, which are written by hand. This paper describes a classification method for on-line handwritten digits and off-line handwritten digits in same time using Genetic Algorithm.
Genetic Algorithms (GAs), are search procedures that use the mechanics of natural selection and natural genetics, have been used in this paper to solve numbers recognition problem. The genetic algorithm treats numbers as a binary string of [6 x 10] pixels and by the process of mating and mutating; the input string is matched to the closest existing character in a database. The proposed method is tested on a sample of 500 digits written by 10 different persons and found to perform satisfactorily most of the time; this paper realized a high percentage of 85%.
