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Robust Visual Odometry System for Illumination Variations Using Adaptive Thresholding

적응적 이진화를 이용하여 빛의 변화에 강인한 영상거리계를 통한 위치 추정

  • Hwang, Yo-Seop (Department of Electronic Engineering, Pusan National University) ;
  • Yu, Ho-Yun (Department of Electronic Engineering, Pusan National University) ;
  • Lee, Jangmyung (Department of Electronic Engineering, Pusan National University)
  • 황요섭 (부산대학교 전자전기컴퓨터공학과) ;
  • 유호윤 (부산대학교 전자전기컴퓨터공학과) ;
  • 이장명 (부산대학교 전자전기컴퓨터공학과)
  • Received : 2015.12.24
  • Accepted : 2016.07.03
  • Published : 2016.09.01

Abstract

In this paper, a robust visual odometry system has been proposed and implemented in an environment with dynamic illumination. Visual odometry is based on stereo images to estimate the distance to an object. It is very difficult to realize a highly accurate and stable estimation because image quality is highly dependent on the illumination, which is a major disadvantage of visual odometry. Therefore, in order to solve the problem of low performance during the feature detection phase that is caused by illumination variations, it is suggested to determine an optimal threshold value in the image binarization and to use an adaptive threshold value for feature detection. A feature point direction and a magnitude of the motion vector that is not uniform are utilized as the features. The performance of feature detection has been improved by the RANSAC algorithm. As a result, the position of a mobile robot has been estimated using the feature points. The experimental results demonstrated that the proposed approach has superior performance against illumination variations.

Keywords

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