The project develops hardware for image processing, image understanding, and machine vision, that will achieve significant performance increases over current systems by implementing a set of operations required to support a specific set of algorithms. These algorithms are intended to process and analyze multiple vectors of:Xd age partial derivative images or "Jet bundles" in parallel. These; t provide a framework for describing the local structure of objects in images at a point. The goal of Phase 2 is to construct a prototype Real Time Image Vector Processor (RTIVP) which will process up to 225 partial derivative images produced by another processor, the GNOSSP. Currently under construction, GNOSSP functions as the first stage for the RTIVP. The RTIVP analyzes these jet bundles using vector projection techniques. It will perform these algorithms at real-time video frame rates with a 640 x 480 image format. It will make use of commercially available programmable gate array integrated circuits. In its final implementation, it will achieve orders of magnitude~0 performance increases over-currently available systems. The GNOSSP and RTIVP together will process data at over 21 gig-operations per second. Commercial Applications:Robotics: vision systems; @9g999 mammography, pap smears, chest x-rays Security: face recognition, fingerprint identification; Automated inspection: object recognition, object verification; Office automation: OCR, forms recognition, Computer vision research; Military: Automated target tracking.
