Morphological co-processing unit for embedded devices

This paper focuses on the development of a fully programmable morphological coprocessor for embedded devices. It is a well-known fact that the majority of morphological processing operations are composed of a (potentially large) number of sequential elementary operators. At the same time, the industrial context induces a high demand on robustness and decision liability that makes the application even more demanding. Recent stationary platforms (PC, GPU, clusters) no more represent a computational bottleneck in real-time vision or image processing applications. However, in embedded solutions such applications still hit computational limits. The morphological co-processing unit (MCPU) replies to this demand. It assembles the previously published efficient dilation/erosion units with geodesic units and ALUs to support a larger collection of morphological operations, from a simple dilation to serial filters involving a geodesic reconstruction step. The coprocessor has been integrated into an FPGA platform running a server that is able to respond to client's requests over the ethernet. The experimental performance of the MCPU measured on a wide set of operations brings as results in orders of magnitude better than another embedded platform, built around an ARM A9 quad-core processor.