Context driven matching in structural pattern recognition

Publisher Summary This chapter examines the problem of structural pattern recognition using graph structures. To speed up the correspondence problem, the chapter proposes a histogram technique which characterizes the context of a primitive within a pattern and allows indexing in the model database with polynomial complexity. The chapter presents a new iterative matching technique based on a histogram of structural context information. Experiments show a good noise suppressing ability while retaining adequate recognition results with minimal false alarms. Because scene primitives are structurally mapped onto the model, orientation and scale can be hypothesized from a match, whereas the model can be used to direct a search for missing information, thereby improving or ignoring the match. This will be the subject for further work.