Hardware acceleration of image and video processing on xilinx zynq platform

Abstract

Advancements in image and video processing are growing over the years for industrial robots, autonomous vehicles, indexing databases, surveillance, medical imaging and computer-human interaction applications. One of the major challenges in real-time image and video processing is the execution of complex functions and high computational tasks. In this paper, the hardware acceleration of different filter algorithms for both image and video processing is implemented on Xilinx Zynq®-7000 System on-Chip (SoC) device. It consists of Dual-core Cortex™-A9 processors which provide computing ability to perform I/O and processing functions and software libraries using Vivado® High-Level Synthesis (HLS). In the proposed work, Sobel-Feldman filter, posterize and threshold filter algorithms are implemented for 1920 ☓ 1080 image resolutions. The implementation results exhibit effective resource utilization such as 45.6% of logic cells, 51% of Look-up tables (LUTs), 29.47% of Flip-flops, 15% of Block RAMs and 23.63% of DSP slices under 100 MHz frequency on comparing with previous works.