A lot of research is going on for exploring image segmentation techniques for accurate brain tumor detection and diagnosis that leads to perfect treatment. Among different image segmentation techniques, LRBAC (Localized-Region-Based Active Contour) method and DRLSE DRLSE (Distance Regularization Level Set Evolution) shows promising results. This paper compares performance of LRBAC method with DRLSE for brain tumor segmentation using MR images in terms of performance parameters such as sensitivity to shape of initial curve, execution time and number of iteration required. It is observed that LRBAC is capable for efficient tumor segmentation with less execution time and less number of iterations as compared to DRLSE method. In cases where shape of initial curve is nearly same to the desired targeted object then not only speed but also perfection of segmentation process is high, as in case of approximately oval tumor, the elliptical shape takes less execution time than rectangular shape