Day and night vehicle detection and counting in complex environment

Vehicle counting system has a wide range of applications, from visual surveillance to intelligent transportation. Due to the different lighting conditions during the day and night, there is not a unified method to capture vehicles. To address this problem, we present unified vehicle detection and counting algorithm based on a new multiple feature background models using morphology and color difference in this paper. Novel Contributions of this paper include: i) unified vehicle detection and counting algorithm based on the proposed feature background model, ii) using the morphology filters to highlight the vehicles both in day and night time, and iii) integrating a color difference features to capture vehicles. The developed system has been implemented on an experiment camera and preliminarily tested in different situations. The experiments on a large number of highway scenes demonstrate that the proposed fast algorithm is robust to illumination and background changes compared to the competing works.