Parallel map recognition based on multilayer partitioned blackboard model

Addresses a parallel recognition paradigm to extract road information from urban map images. The main objective is to make clear the applicability between data parallelization and function parallelization in the road extraction process. We introduce the multilayer partitioned blackboard model. This model manages relationships among the corresponding partitioned segments in different layers of the blackboard so as to perform easily the cooperation among different processing procedures. Namely, individually partitioned segments in each layer are applicable to implement the data parallelization, while the relationships between corresponding partitioned segments in different layers support the cooperative control mechanism of function parallelization effectually