Architectural requirements of image understanding with respect to parallel processing

An overview of the architectural requirements for parallel processing in support of real-time, knowledge-based computer vision is given. One of the goals of this work is to provide an appreciation for the diversity, complexity, and computational intensity of vision processing. It begins with a description of common vision algorithms, analyzes their requirements in terms of the inherent structures that are present, and relates them to computation, communication, and control in parallel processing. After concluding that traditional architectural approaches to parallel processors are suboptimal, discussion focuses on heterogeneous processors. Different forms of parallelism can be applied at three levels of computational granularity, each having unique requirements and corresponding to levels of abstraction in the image interpretation process. In addition, interaction between levels must take place via parallel data and control paths. The paper concludes with a brief discussion of image understanding architecture, a multilevel parallel processor designed for image understanding