SoC processor for real-time object labeling in life camera streams with low line level latency

Image recognition systems implement a number of processing stages: preprocessing, segmentation and classification. In camera based video processing chains, usually several frame delays are incurred between the moment of capture and the actual availability of the classification results. Hardware architectures for stream based video processing have already been widely employed. In this paper, a new hardware architecture for accelerating the generic task of connected component analysis and object labeling in the segmentation step is presented. The architecture is specifically optimized for very low latency between image component capture by a camera and the detection in hardware. This latency constitutes only a few delay lines, thereby shortening the response time by a few orders of magnitude in comparison to traditional frame-buffer based methods.