Over recent years, iris recognition has been an explosive growth of interest in human identification due to its high accuracy. Iris recognition is a biometric system that uses iris to verify and identify human identity. Iris has pattern that is rich with textures and can be compared among humans. There are many methods can be used in iris recognition. The methods based on the integro-differential operator and Hough transform are the most widely used in iris recognition. Unfortunately, both methods require more time to execute and has less accurate recognition accuracy due to the eyelid occlusion. In order to solve these problems, the Chan-Vese active contour is modified to reduce the execution time and to increase the recognition accuracy of iris recognition. Then, this method is compared with the integro-differential operator method. The iris images from CASIA-v4 database are used for the experiments. According to the results, the proposed method recorded 0.91 s for execution time which was 61.28 % faster than the integro-differential operator method. The proposed method also achieved 0.9831 for area under curve (AUC) which was 2.66 % higher recognition accuracy than the integro-differential operator method. To conclude, the modified Chan-Vese active contour was able to improve the performance of iris recognition compared to the integro-differential operator method.