Aim: To recognise the currency value accurately using the machine learning algorithms support vector machine and analyze the accuracy with the Decision Tree. Materials and Methods: Currency recognition using support vector machine (n=10) and Decision Tree (n=10) which are machine learning algorithms. Here the pretest power analysis was carried out with gpower 80% and the sample size for the two groups is 20. Results: Currency recognition system was done with the support vector machine and Decision Tree with the accuracy of 87.09% and 80.64% respectively. From the experiment, it has the statistical 2-tailed significant difference in the accuracy of the two algorithms is 0.001 (p<0.05) by performing independent samples t-tests. Conclusion: Support Vector Machine executes significantly better than the Decision Tree in currency recognition system.