Real-time object specific recognition via raster scan video processing

Most real-time video recognition systems have historically relied upon region of interest processing based on low level properties such as pixel color to quickly reduce the computational load required for real-time performance. Because these low level properties are quite sensitive to lighting variations, they are limited in their application scope. This paper presents an approach which segments objects of interest via higher level relational properties overcoming such limitations. These relations are autoassociatively and incrementally constructed through a processing structure called raster scan video processing in a hierarchical manner. Relational properties of interest are then obtained with local object specific processes. The compactness of this processing structure has allowed it to be implemented on one TMS320C40 digital signal processing chip at a processing rate of three frames per second. The approach is applied to the problem of road sign recognition in realistic outdoor scenes. Video frame recognition results for stop and pedestrian signs are presented along with details of the DSP implementation. (C) 1999 Academic Press.