A rail detection algorithm based on pair particles filtering

Abstract

Safety of mass transportation like train cannot be emphasized enough, and accurate rail detection in the direction of progress can be useful to the safe operation of a train. In this paper, we propose a new pair particles filtering based rail detection algorithm that simultaneously predicts a pair position of left and right rails. Multiple pairs of particles are first generated from the previously detected rails, and features of a pair particles position, rail gauge, and gradient magnitude are used to detect the positions of pair rails. The proposed pair particles filtering based method flexibly detects both straight and curved rails robustly. Experiments with various actual rail images show plausible detection results of the proposed method.