AbstractsComputer Science

Enhancing long, thin, sinuous structures in images is a common problem in image analysis. Mathematical morphology is often used to solve this problem. One approach is known as the path opening. The goal of this project was to investigate whether a preselection of a limited number of paths, based on the upper skeleton of the image, could be used to find an approximate, faster path opening. In this thesis, a new, graph-based algorithm, that is the result of this investigation, is presented. The new algorithm is compared with the traditional path opening and, to some extent, with the parsimonious path opening. Experiments suggest that the implemented algorithm is faster for increasing path length, and runs in linear time with respect to image size. They also suggest that the new algorithm is similar to the traditional path opening when measuring length distributions, while being orders of magnitude faster, thereby making it comparable in speed to the parsimonious path opening, while mitigating the problem of blind spots that the parsimonious path opening suffers from.