Showing papers by "Stan Z. Li published in 1993"

Automatic registration of aerial photographs and digitized maps

Abstract: We have developed a method of matching and recognizing aerial road network images based on road network models. The input is a list of line segments of an image obtained from a preprocessing stage, which is usually fragmentary and contains extraneous noisy segments. The output is the correspondences between the image line segments and model line segments. We use attributed relational graphs (ARG) to describe images and models. An ARG consists of a set of nodes, each node representing a line segment, and attributed relations between nodes. The task of matching is to find the best correspondences between the image ARG and the model ARG. The correspondences are found using a relaxation labeling algorithm, which optimizes a criterion of similarity. The algorithm is capable of subgraph matching of an image road structure to a map road model covering an area 10 times larger than the area imaged by the sensor, provided that the image distortion due to perspective imaging geometry has been corrected during preprocessing stages. We present matching experiments and demonstrate the stability of the matching method to extraneous line segments, missing line segments, and errors in scaling.

Self-organization of surface shapes

Abstract: A problem in surface modeling and approximation is how to sample a surface into a set of significant points. It is desirable that the sampling is done in such a way that best preserves the original shape. A principle is that highly curved area should be sampled densely and vice versa. This paper presents a self-organization method for automated surface sampling in this principle. Given a scale shape function of local curvedness of the surface and a number of samples, the set of optimal locations of sample points is defined as the solution to a system of nonlinear equations. The solution can be found using a simple iterative algorithm involving no free parameters. The algorithm forms topology-preserving meshes from random initialisation. Mesh spacing vs. surface curvedness can be easily controlled by a single parameter in the shape function. Key locations can be prescribed by imposing additional boundary conditions. Experiments are presented with synthetic data.