A novel Q-scanning for convex hull algorithm

Convex hull is one of the important part of computational geometry. Many applications have used this method as part of their system. In this research, the novel Q-scanning of convex hull algorithm is proposed. The algorithm reduces computational complexity of conventional convex hull algorithm. The initial step of the proposed method is dividing the problem of convex hull into four subset hull. Each hull has its extreme point. In the process, the extreme point will move until meet convergence. The proof of the concept is conducted in Matlab software. The method of the experimental setup is a convex construction hull from some finite points of natural number which set randomly. The experiment shows that the algorithm is able to build a convex hull with O(n) of computational complexity and can be used as alternative approach for convex hull problem.