Computational analysis of Canny & Binary Fuzzy Rough Set model based on Triangle Modulus Edge Detectors

In this work we present a formal comparative over the computational complexity of two edge detectors, in one hand the Canny Edges Detector and on the other an edges detector based on Rough Sets Theory which has been proved as very efficient from the results point of view, so we are now interested in their performances, i.e., we have developed an analysis from the computational point of view. To develop such study we have used ROSA Analyser tool which generates the Labelled Transition System, LTS, corresponding to a process specified in the Markovian Process Algebra ROSA. ROSA Analyser takes as input the syntactical representation of the process and once its syntactical structure has been properly layered represented -internally- by the tool, it applies the Operational Semantics of ROSA, so producing the corresponding LTS, which shows all the possible behaviours of the system we are interested in. A clear advantage, also from the computational point of view, of the encoder using Rough Sets Theory has been found.