A Vision-Based Vehicle Identification System

This paper presents a vision-based vehicle identification system which consists of object extraction, object tracking, occlusion detection and segmentation, and vehicle classification. Since the vehicles on the freeway may occlude each other, their trajectories may merge or split. To separate the occluded objects, we develop three processed: occlusion detection, motion vector calibration, and motion field clustering. Finally, the segmented objects are classified into seven different categorized vehicles.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Chung-Lin Huang, Wen-Chieh Liao
• Keywords: Computer Vision, ICPR 2004, Motion Vector Calibration, Occlusion Detection, Vision-based Vehicle Identification