Real-Time Processing of Structure and Its Anticipation

A two-level processing scheme for real-time image understanding is proposed, where an example-based (or case-based) reasoning in neural AI systems is introduced. The system has two levels; Component Level and Structure Level. At the component level, an elementary pattern recognition is performed as in the conventional pattern recognition, while the syntax pattern recognition is done at the structure level. Both levels are essentially time-consuming (theoretically, NP-complete each). The pattern recognition assisted by syntax recognition reduces the total complexity of processes, and the system can perform a real-time image understanding, when the VLSI chips are introduced. As a result, we show a reasonable real-time image understanding scheme by introducing neural pattern recognition at the component level and a case-based AI technique at the structure level.