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New Approach to Two-wheeler Detection using Correlation Coefficient based on Histogram of Oriented Gradients

  • Lee, Yeunghak (Department of Avionics Engineering College of Aviation, Kyungwoon University) ;
  • Shim, Jaechang (Department of Computer Engineering, College of Engineering, Andong National University)
  • Received : 2016.12.18
  • Accepted : 2016.12.31
  • Published : 2016.12.31

Abstract

This study aims to suggest a new algorithm for detecting two-wheelers on road that have various shapes according to the viewing angle for vision based intelligent vehicles. This article describes a new approach to two-wheelers detection algorithm riding on people based on modified Histogram of Oriented Gradients (HOG) using correlation coefficient (CC). The CC between two local area variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using HOG which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the CC between the area of each cell and one of two-wheelers, can be extracted as the weighting factor in process for normalizing the modified HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

Keywords

References

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