The pyramid architecture is shown by simulation to be an effective architecture for a wide range of computer vision tasks from low level pixel-oriented operations to segmentation to high level symbolic operations.
Results also show that processing overhead for a task can take more time than the task itself.
This processing overhead includes the loading of convolution kernels and morphological look-up tables. An object-oriented methodology for modeling the individual processors and ports is used. The method for modeling and constructing the prototype is efficient and flexible. This encourages the fine-tuning of the architecture design. The prototype is used as a testbed for simulations of computer vision tasks and the results of these simulations are presented.