A run-length encoding co-processor for retinal image texture analysis

This paper presents a Zynq-based system to compute Run-Length encoding Matrix features for retinal image texture analysis. In order to improve the performance of the software implementation, we propose a co-processor architecture implemented in the programmable logic portion of the Zynq platform. Experimental results show a speedup of 26.3× with respect to the software version implemented on the ARM processor alone, for 2496 × 1664 images. The additional area to implement the co-processor is limited to 13% of DSP48E1s slices and about 2% for LUTs and flip-flops.