Analysis of the interaction between edge and line finding techniques

摘要

Edge and line detection are important processes in many computer vision systems. This paper examines errors in each of these processes and how they are related, i.e. how do errors in edge detection propagate to cause errors in line detection. Much use is made of simulated images which produce ground truth information, allows many trials to be performed, and allows analysis of variance. The analysis is restricted to polyhedral models which is appropriate for line finding algorithms. Results are presented that show how edge error affects line error, which error dominates for one variable, and how the errors vary for one parameter namely the scale or sigma for the edge detector. A hypothesis addressed is whether knowing the performance of edge and line detectors independently with respect to ground truth allows the overall performance of the two processes on real data to be predicted.