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A Study on a effective Information Compressor Algorithm for the variable environment variation using the Kalman Filter

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2018, 23(4), pp.65-70
  • DOI : 10.9708/jksci.2018.23.04.065
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : April 3, 2018
  • Accepted : April 10, 2018
  • Published : April 30, 2018

Jae-Yun Choi 1

1한국폴리텍대학 인천캠퍼스

Accredited

ABSTRACT

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

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