Fundus image processing is getting widely used in retinopathy detection. Detection approaches always proceed to identify the retinal components, where optic disk is one of the principal ones. It is characterized by: a higher brightness compared to the eye fundus, a circular shape and convergence of blood vessels on it. As a consequence, different approaches for optic disk detection have been proposed. To ensure a higher performing detection, those approaches varied in terms of characteristics set chosen to detect the optic disk. Even the performances are slightly different, we distinguish a significant gap on the computational complexity and hence on the execution time. This paper focuses on the survey of the approaches for optic disk detection. To identify an efficient approach, it is relevant to explore the chosen characteristics and the proposed processing to locate the optic disk. For this purpose, we analyze the computational complexity of each detection approach. Then, we propose a classification approach in terms of computational efficiency. In this comparison study, we distinguish a relation between computational complexity and the characteristic set for OD detection.