Open Access

ARTICLE

Hardware Acceleration of Image and Video Processing on Xilinx Zynq Platform

Praveenkumar Babu, Eswaran Parthasarathy^*

Department of Electronics and Communication Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, 603203, India

* Corresponding Author: Eswaran Parthasarathy. Email:

Intelligent Automation & Soft Computing 2021, 30(3), 1063-1071. https://doi.org/10.32604/iasc.2021.018903

Received 25 March 2021; Accepted 11 May 2021; Issue published 20 August 2021

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.

---

Keywords

---