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The FE-SM/SONN for Recognition of the Car Skid Mark

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2012, 17(1), pp.125-132
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Koo Gun Seo 1

1숭의여자대학

Accredited

ABSTRACT

In this paper, We proposes FE-SM/SONN for recognizing blurred and smeared skid mark image caused by sudden braking of a vehicle. In a blurred and smeared skid marks, tread pattern image is ambiguous. To improve recognition of such image, FE-SM/SONN reads skid marks utilizing Fuzzy Logic and distinguishing tread pattern SONN(Self Organization Neural Networks) recognizer. In order to substantiate this finding, 48 tire models and 144 skid marks were compared and overall recognition ratio was 89%. This study showed 13.51% improved recognition compared to existing back propagation recognizer, and 8.78% improvement than FE-MCBP. The expected effect of this research is achieving recognition of ambiguous images by extracting distinguishing features, and the finding concludes that even when tread pattern image is in grey scale, Fuzzy Logic enables the tread pattern recognizable.

Citation status

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