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This paper presents an online signature verification system based on Genetic Algorithm-Support Vector Machine (GA-SVM). The raw information, obtained from SVC 2004 database, as time functions is used to derive 75 features. Six different groups of features have been generated from 75 features and their performance evaluated using SVM. A method is proposed to reduce the computational complexity and the amount of memory required without compromising on accuracy using the sub set of features selected by Genetic Algorithm as the input to SVM. The experimental results show that this method provides good performance in terms of accuracy and memory requirement.