Segmentation and Estimation of Surface from Statistical Probability of Object Features

This paper presents an approach to segment an image into areas of surfaces, and to compute the surface properties from a gray-scale image in order to describe the surfaces for reconstruction of the 3-D shape of the objects. At first edges are extracted from a gray-level image as many as possible. Next, the other characters of a surface (color, coordinates and image intensity) are extracted. These features of a surface on a pixel of an image plane are mapped to a point of the feature space, and segmented to several groups by cluster analysis on this space. Finally, the states of object surface in 3-D space are computed from distributional probability of local and overall statistical features of a surface.