An Effective and Visualized State Detection of Metro Vehicle Door System

Abstract

Metro Vehicle Door System (MVDS) is one of the most frequently used parts in rail transit. In this work, we propose an effective and visualized state detection technique of MVDS by utilizing feature extraction and matching, which is helpful to improve the safety and reliability of the door system. Five states of MVDS, the normal opening, opened, closing and closed state, as well as the anti-extrusion (also named as anti-drag) state, are to be detected in our work. In particular, we design an improved Speeded Up Robust Features (SURF) method to reduce the mismatching pairs by exploiting local space distance, which is crucial for practical usage. Furthermore, we present a scheme to detect the five states of MVDS mentioned above via our improved SURF. Finally, we conduct experiments in subjective and objective, and the resultant performance shows the effectiveness of our method.