This paper addresses the problem of neural-network-based control mechanism of Blackboard of image understanding system.Blackboard architecture has been used as a model for intelligent information fusion in π

A feedforward neural network model was proposed as the Backboard control mechanism of π. The blackboard architecture was developed to deal with the difficult characteristics of the speech understanding problem: a vary large search space: erroneous or incomplete input data

and imprecise and/ or incomplete problem-solving knowledge and it has proven to be popular for AI problems. The image understanding system requires a problem-solving model that supports the incremental development of solutions

can apply diverse types of knowledge

and can adapt its strategy to the particular problem situation. The neural-network-based control mechanism of the blackboard can offer efficient control for information extraction by image understanding system π.