期刊名称：International Journal of Software Engineering & Applications (IJSEA)
印刷版ISSN：0976-2221
电子版ISSN：0975-9018
出版年度：2012
卷号：3
期号：3
页码：17
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Nowadays, number of vehicles has been increased and traditional systems of traffic controlling couldn’t beable to meet the needs that cause to emergence of Intelligent Traffic Controlling Systems. They improvecontrolling and urban management and increase confidence index in roads and highways. The goal of thisarticle is vehicles classification base on neural networks. In this research, it has been used a immovablecamera which is located in nearly close height of the road surface to detect and classify the vehicles. Thealgorithm that used is included two general phases; at first, we are obtaining mobile vehicles in the trafficsituations by using some techniques included image processing and remove background of the images andperforming edge detection and morphology operations. In the second phase, vehicles near the camera areselected and the specific features are processed and extracted. These features apply to the neural networksas a vector so the outputs determine type of vehicle. This presented model is able to classify the vehicles inthree classes; heavy vehicles, light vehicles and motorcycles. Results demonstrate accuracy of thealgorithm and its highly functional level.
