A parallel hardware design for parametric active contour models

We propose a hardware design for parametric active contour models particularly applicable for implementation of gradient vector flow (GVF) snakes. A numerical iterative algorithm of GVF is used to develop a parallel hardware design in a FPGA architecture which is based on using a number of parallel cell units for snake points and a main controller for all control tasks and memory accesses. Using this parallel architecture we could obtain a snake adaptation time of 22 ms in QVGA image size (320/spl times/240 pixels) which was used for motion detection in video samples of 20 fps. The performance results are very encouraging, however, the system can be still improved by using more parallel architecture and simplifying some complicated instructions.