A connectivity solution for extraction of thin objects

Image processing has frequently to deal with thin structures that hold the information required. In natural images, there is a wide variability of conditions and the borders of objects are not always well defined. Progressive scan, an algorithm derived from fuzzy-connectedness theory, is described here as a specific case of more general χ-connectedness. Exploiting some analogies to the mechanical world, it allows one to track thin structures and consequently, is suitable for river, motorway or vessel extraction. In the computation of fuzzy connectedness, a widely used approach is based on an adaptive growing mechanism that follows the best paths starting from a reference seed point. The new algorithm uses three or more seed points in order to better drive that approach along the structure of interest. Results of the algorithm are the best path along an object and a connectivity map. The algorithm can deal with heterogeneous images ranging from medical to remote sensed ones.