A Convenient Vision-Based System for Automatic Detection of Parking Spaces in Indoor Parking Lots Using Wide-Angle Cameras

Abstract

A convenient indoor vision-based parking lot system using wide-angle fisheye-lens or catadioptric cameras is proposed, which is easy to set up by a user with no technical background. Easiness in the system setup mainly comes from the use of a new camera model that can be calibrated using only one space line without knowing its position and direction, as well as from the allowance of convenient changes in detected parking space boundaries. After camera calibration based on the new camera model is completed, parking space boundary lines are automatically extracted from input wide-angle images by a modified Hough transform with a new cell accumulation scheme, which can generate more accurate equal-width curves using the geometric relations of line positions and directions. In addition, the user may easily add or remove the boundary lines by single clicks on images, and parking spaces can be segmented out by region growing with the use of the boundary lines. Finally, vacant parking spaces can be detected by a background subtraction scheme. A real vision-based parking lot has been established and relevant experiments conducted. Good experimental results show the correctness, feasibility, and robustness of the proposed methods.