Background Extraction and Vehicle Detection Method Based on Histogram in YCbCr Color Space

Abstract

In computer vision-based Intelligent Transportation Systems (ITS), one of the key techniques is to detect the vehicles accurately. In this paper, we propose a background extraction and vehicle detection method based on histogram in YCbCr color space. By using YCbCr color space, the influence of illumination change and shadows is reduced. To solve the problem with change in background itself, we propose a background update method by using the pixel change count and histogram. Experiment results show that the proposed algorithm can effectively extract and update the background information in complicated urban traffic environment. It also improves the accuracy of vehicle detection.

Image Processing Technique for Traffic Density Estimation

“…The experimental results show that the proposed background construction scheme is superior to traditional background construction and can produce a better quality image. The algorithm is simpler than the other algorithms, such as: the algorithm based on the sigma-delta filter [13], the algorithm based on combining the Median-based estimation and Support Vector Machines [14] and the algorithm based on histogram in YCbCr color space [15]. Besides, the new proposed background method quickly updated.…”