Iterative vanishing point estimation based on DBSCAN for omnidirectional image

Abstract

Regarding the autonomous of robot navigation, vanishing point (VP) plays an important role in visual robot applications such as iterative estimation of rotation angle for automatic control as well as scene understanding. Autonomous navigation systems must be able to recognize feature descriptors. Consequently, this navigating ability can help the system to identify roads, corridors, and stairs; ensuring autonomous navigation along the environments mentioned before the vanishing point detection is proposed. In this paper, the authors propose solutions for finding the vanishing point in real time based density-based spatial clustering of applications with noise (DBSCAN). First, we proposed to extract the longest segments of lines from the edge frame. Second, the set of intersection points for each pair of line segments are extracted by computing Lagrange coefficients. Finally, by using DBSCAN the VP is estimated. Preliminary results are performed and tested on a group of consecutive frames undertaken at Nam-gu Ulsan, South Korea to prove its effectiveness.