Real time image segmentation using FPGA and parallel processor

We present in this paper the realization of a classification board, for real-time image segmentation. The classification of each pixel is completed using a real time extraction of attributes and a geometric classification method by stress polytope training, which ensures a high decision speed (100 ns per pixels) and good performance. The decision operator has been integrated in the form of a full custom circuit, and the extraction of parameters is performed using a single high density FPGA