Mixture of gaussians-based background subtraction for bayer-pattern image sequences

Jae Kyu Suhr, Ho Gi Jung, Gen Li, Jaihie Kim

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)

Abstract

This letter proposes a background subtraction method for Bayer-pattern image sequences. The proposed method models the background in a Bayer-pattern domain using a mixture of Gaussians (MoG) and classifies the foreground in an interpolated red, green, and blue (RGB) domain. This method can achieve almost the same accuracy as MoG using RGB color images while maintaining computational resources (time and memory) similar to MoG using grayscale images. Experimental results show that the proposed method is a good solution to obtain high accuracy and low resource requirements simultaneously. This improvement is important for a low-level task like background subtraction since its accuracy affects the performance of high-level tasks, and is preferable for implementation in real-time embedded systems such as smart cameras.

Original languageEnglish
Article number5604673
Pages (from-to)365-370
Number of pages6
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume21
Issue number3
DOIs
Publication statusPublished - 2011 Mar

Bibliographical note

Funding Information:
Manuscript received March 5, 2010; revised May 26, 2010; accepted July 2, 2010. Date of publication October 18, 2010; date of current version March 23, 2011. This work was supported by the National Research Foundation of Korea through the Biometrics Engineering Research Center, Yonsei University, under Grant R112002105070020(2010). This paper was recommended by Associate Editor B. Zeng.

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Electrical and Electronic Engineering

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