Local reasoning in fuzzy attribute graphs for optimizing sequential segmentation
In Proceedings of the 6th IAPR TC-15 workshop on graph-based representations in pattern recognition (GBR)
Abstract
Spatial relations play a crucial role in model-based image recognition and interpretation due to their stability compared to many other image appearance characteristics. Graphs are well adapted to represent such information. Sequential methods for knowledge-based recognition of structures require to define in which order the structures have to be recognized. We propose to address this problem of order definition by developing algorithms that automatically deduce sequential segmentation paths from fuzzy spatial attribute graphs. As an illustration, these algorithms are applied on brain image understanding.