Shape from contour using adaptive image selection

Abstract

SUMMARYThe "shape-from-contour method" reconstructs the 3D shape of the surface of an object by extracting its contour from each of a series of successive images of the object. This can be realized by using a CCD camera, and is a relatively accurate method of obtaining environmental information. However, to obtain an accurate result, many images must be processed. Therefore, it is important to select the images depending on their effect on the final result, particularly for high-speed processing.This paper proposes an adaptive image selection (AISE) method which depends on the required accuracy. The method has been applied to objects having various cross-sectional shapes. The errors in shape reconstruction and the number of images required in the conventional method and the proposed method are compared. The experimental results show that the proposed method requires fewer images than the conventional method, particularly when the surface curvature of the object has large variation. The theoretical relationship between the accuracy of the reconstructed shape and the number of images required is also derived.