Development and evaluation of the authentication systems by using different palm print identificaton methods

Information security has become more important after the increase in cyber-crimes. Thus, all corporations today are using person- recognition systems. Plenty of software products have been developed in order not to allow personal information to be confused with another one by means of different ways and algorithms. These software products use unique specialties such as DNA, iris, fingerprint and palm print. They differ in direct proportion to how much the corporation needs information security and how much it invests. The most important part is to have a clear characteristic from the person. Today, palm print recognition systems are started to be used commonly. The aim of this paper is to design a palm print recognition system by using textural features and it aims maximum correctness. Two different systems were designed with this aim. In the first system, features were extracted by passing it through Gabor filter. Classification was made by using a simple linear discriminant analysis algorithm with these features. In the second system, text features were found by using GLCM and Hu's methods. These features were classified separately by using a simple linear discriminant analysis algorithm. Data was taken from CASIA database in this study.