SoC hardware implementation of real-time video segmentation based on the mixture of Gaussian algorithm

Peng Li, Hua Tang

Research output: Contribution to journalArticlepeer-review

Abstract

Video segmentation based on the Mixture of Gaussian (MoG) algorithm is widely used in video processing systems, and hardware implementations have been proposed in the past years. Most previous work focused on high-performance custom design of the MoG algorithm to meet real-time requirement of high-frame-rate high-resolution video segmentation tasks. This paper focuses on the System-on-Chip (SoC) design and the priority is SoC integration of the system for flexibility/adaptability, while at the same time, custom design of the original MoG algorithm is included. To maximally retain the accuracy of the MoG algorithm for best segmentation performance, we minimally modified the MoG algorithm for hardware implementation at the cost of hardware resources. The MoG algorithm is custom-implemented as a hardware IP (Intellectual Property), which is then integrated within an SoC platform together with other video processing components, so that some key control parameters can be configured on-line, which makes the video segmentation system most suitable for different scenarios. The proposed implementation has been demonstrated and tested on a Xilinx Spartan-3A DSP Video Starter Board. Experiment results show that under a clock frequency of 25 MHz, this design meets the real-time requirement for VGA resolution (640 × 480) at 30 fps (frame-per-second).

Original languageEnglish (US)
Article number12
JournalJournal of Low Power Electronics and Applications
Volume7
Issue number2
DOIs
StatePublished - Jun 2017

Bibliographical note

Funding Information:
The study was funded by the Intelligent Transportation Systems (ITS) Institute, a program of the University of Minnesota’s Center for Transportation Studies (CTS). Financial support was provided by the United States Department of Transportation’s Research and Innovative Technologies Administration (RITA). The project was also supported by the Northland Advanced Transportation Systems Research Laboratories (NATSRL), a cooperative research program of the Minnesota Department of Transportation, the ITS Institute, and the University of Minnesota Duluth Swenson College of Science and Engineering.

Publisher Copyright:
© 2017 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Hardware implementation
  • Mixture-of-gaussian algorithm
  • System-on-chip
  • Video segmentation
  • Video signal processing

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