Abstract: This paper presents a new vehicle detection method from images acquired by cameras embedded in a moving vehicle. Given the sequence of images, the proposed algorithms should detect out all cars in realtime. Related to the driving direction, the cars can be classified into two types. Cars drive in the same direction as the intelligent vehicle (IV) and cars drive in the opposite direction. Due to the distinct features of these two types, we suggest to achieve this method in two main steps. The first one detects all obstacles from images using the so-called association combined with corner detector. The second step is applied to validate each vehicle using AdaBoost classifier. The new method has been applied to different images data and the experimental results validate the efficacy of our method.

Zebbara Khalid, Abdenbi Mazoul and Mohamed El Ansari, “A new vehicle detection method” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Artificial Intelligence, 2011. http://dx.doi.org/10.14569/SpecialIssue.2011.010312

@article{Khalid2011,
title = {A new vehicle detection method},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Artificial Intelligence}
doi = {10.14569/SpecialIssue.2011.010312},
url = {http://dx.doi.org/10.14569/SpecialIssue.2011.010312},
year = {2011},
publisher = {The Science and Information Organization},
volume = {1},
number = {3},
author = {Zebbara Khalid and Abdenbi Mazoul and Mohamed El Ansari},
}