In recent years, video and image analysis tools have been increasingly employed in many real-time applications; these include lane and car recognition for intelligent transportation systems, human object segmentation and tracking for intelligent video surveillance systems, and face detection and image indexing for digital still cameras and camcorders. To implement these analysis tools in real-time applications, new computing architectures such as reconfigurable architectures,

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... c instruction-set processors, stream processing architectures, and dedicated processing elements have been developed to handle more complex real-time content analysis. It is often necessary to integrate specially designed hardware accelerators with other processors to achieve a high processing speed. Furthermore, new algorithms that are suitable for hardware design or implementation on existing architectures play important roles in such systems. The purpose of this special issue is to report on new hardware design ideas to support these video and image analysis tools. This special issue contains two parts. The first part describes computing platform design, including vision processors and memory sub-system design. The second part describes several design case studies of image and video analysis systems, including machine learning engines and video segmentation engines.