A HYBRID SYSTEM FOR 2-DIMENSIONAL IMAGE RECOGNITION

In this paper, after briefly considering the reasons that prevented th e development of hybrid systems for signal processing (SP), we point o ut the requirements for their future exploitation. The need for a bett er knowledge of different approaches in the scientific community and t he definition of methodologies for designing hybrid systems' are highl ighted as two key points. Then we suggest that the well-blown ''task-s tructure analysis'' design technique should be modified to make it sui table for hybrid systems. The proposed modification is based on the ma in need to choose the roles of different approaches and the mechanisms to integrate them. As an example, we describe the design of a hybrid system for two-dimensional (2 D) image recognition; the system is base d on the integration of a numerical, a symbolic, and a connectionist a pproach. We detail the integration of the symbolic and connectionist a pproaches to the generation of the models of the objects to be recogni zed. We describe the main problems involved and the solutions adopted. In particular, we exploit the synergistic aspects of the two approach es in oi dei to overcome the bottleneck of knowledge acquisition. Fina lly, we report experimental results on two applications to show some a dvantages of the proposed hybrid system.