A radius/center constraint Fuzzy C-Spherical Shell clustering (FCSS) algorithm is presented for the circle detection problem in digital image processing and computer vision. FCSS substitutes spherical shells for points as the prototype based on conformal geometric algebra, and the inner product of patterns and spherical shells in conformal space is equal to the distance from the patterns to spherical shells. Meanwhile, FCSS represents the membership between the patterns and its spherical shells by the introduction of fuzzy membership. Then the objective function for radius/center constraint FCSS clustering analysis is expressed, and a unified solution to minimize this constraint objective function is deduced. Experimental results of both artificial data and real image have proved that the clustering algorithm can cluster the spherical shell type data and detect circles in image effectively.