The first step for human face recognition is to locate the head boundary in a head-and-shoulders image. An approach that uses adaptive contour models or "snakes" is described to solve this problem. Since we have a priori knowledge of the shape of a head, this active contour model is tailor-made for representing the head boundary. In this paper, a reliable method to locate the approximate position of the head and to estimate the head boundary is proposed. The effect of the parameters for snakes is investigated by locating the head boundary, and a best set of the parameters is suggested. A fast algorithm based on the greedy algorithm for active contour modeling is also presented. The computational complexity of this new algorithm is analyzed and compared with the greedy algorithm. This fast algorithm has a performance capability comparable to the greedy algorithm and reduces the execution time by more than 30% on the average.