An Organic Computing architecture for visual microprocessors based on Marching Pixels

The paper presents architecture and synthesis results for an organic computing hardware for smart CMOS camera chips. The organic behavior in the chip hardware is based on distributed and emergent functionality exploited for detection of objects and their center points given in binary images. Future real-time embedded systems used in industrial image processing have to provide reply times in the range of milliseconds. It is impossible to meet such strict requirements for megapixel resolutions with serial processing schemes in particular if multiple given objects have to be detected. Even classical parallel techniques like SIMD or MIMD approaches are not sufficient due to their dependency on more or less central control structures. To achieve more flexibility, unlimited scalability and higher performance parallel emergent architectures are necessary. We present such an approach, denoted as marching pixels, for future digital visual microprocessors. Marching pixels work similar to artificial ants. They are crawling as hardware agents within a pixel field, e.g. to identify and to detect center points of an arbitrary number of objects given in an image. We present an emergent marching pixel algorithm for the processing of arbitrary concave objects and its mapping onto real hardware. Based on synthesis results for FPGAs and ASICs we discuss the possibilities of digital organic computing approaches for visual microprocessors for future smart high-speed camera systems.