Semi-implicit method of fast active contour models using iterative method for edge detection
Norma Binti Alias, Rosdiana Shahril · International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering · 2011
In computational vision research, low-level tasks such as edge detection, stereo matching, and motion tracking have been widely emphasis as autonomous bottom-up processes. Active contours have also been widely applied for various applications in medical image processing. Semi-implicit AOS is very stable constraint on the size of the time step associated with explicit numerical schemes and will be adopted in our implementation. The proposed algorithm using iterative methods such as Jacobi, Gauss-Seidel and SOR will be implementing in object edge detection experiments performed on MRI images. MATLAB has been chosen as computational platform for the experiment implementation. It is well suited and widely used in the medical image processing for the monitoring and detection. The experimental results of the edge detection on medical images are illustrated in analysis section. As the conclusion the iterative method is the alternative scheme instead using direct method for accurate contours tracking of the medical image processing.