Minimal Paths by Sum of Distance Transforms
Minimal path extraction is a frequently used tool in image processing with applications in for example centerline extraction and edge tracking. This paper presents results and methods for i extracting minimal paths and for ii utilizing local direction in the minimal path computation. Minimal path extraction is based on sum of distance transforms resulting in a stable method, without need for local decisions, which is needed for methods based on backtracking. Local direction utilization is discrete derivative based concepts such as the structure tensor, the Hessian and the Beltrami framework. The combination of minimal path extraction and local direction utilization gives a strong framework for minimal path extraction.
DGCI