제목

Real-Time Front Vehicle Detection Algorithm Based on Local Feature Tracking Method

저자명

Jaehyoung Yu, Youngjoon Han, Hernsoo Hahn

국문초록

This paper proposes an algorithm that extracts features of the back side of the vehicle and detects the front vehicle in real time by local feature tracking of the vehicle in the continuous images. The features of the back side of vehicle are vertical and horizontal edges, shadow and symmetry, and compared local features using the fixed window size for tracking in the continuous images. It used Haarlike mask that is robust and fast for detecting vertical, horizontal edges and extracted shadow by histogram equalization, and used the sliding window method that compares both side templates of the detected candidates to extract symmetry. The features for tracking are vertical edges, and used histogram to compare location of the peak and magnitude of the edges. The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image, and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown, and it can be performed in real time through applying to the embedded system.

원문 수록처

Jounal of Measurement Science and Instrumentation

자료유형

International Journal