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http://dx.doi.org/10.5302/J.ICROS.2016.15.0218

Robust Visual Odometry System for Illumination Variations Using Adaptive Thresholding  

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)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.22, no.9, 2016 , pp. 738-744 More about this Journal
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
stereo camera; visual odometry; feature detection; adaptive thresholding; mobile robot;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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