| AUTOMATIC VEHICLE RECOGNITION FOR URBAN TRAFFIC MANAGEMENT |
| Paper ID : 1099-SMPR |
| Authors: |
|
Mona Mohammadi *1, Fatemeh Tabib Mahmoudi2 1Dept of Geomatics, Faculty of Engineering, Shahid Rajaee Teacher Training University 2Dept of Geomatics, Faculty of Civil engineering, Shahid Rajaee Teacher Training University, Tehran, Iran |
| Abstract: |
| Automatic vehicle recognition has an important role for many applications such as supervision, traffic management and rescue tasks. The ability of online supervision on the distribution of vehicles in urban environments prevents traffic, which in turn reduces air pollution and noise. However, this is extremely challenging due to the small size of vehicles, their different types and orientations, and the visual similarity to some other objects in very high resolution images. In this paper, an automatic vehicle recognition algorithm is proposed based on very high spatial resolution aerial images. In the first step of the proposed method, by generating the image pyramid, the candidate regions of the vehicles are recognized. Then, performing reverse pyramid, decision level fusion of the vehicle candidates and the classification results of the original image are performed in order to modify recognized vehicle regions. For evaluating the performance of the proposed method in this study, Ultracam aerial imagery with spatial resolution of 11 cm and 3 spectral bands have been used. |
| Keywords: |
| Vehicle Detection, Image pyramid, Segmentation, Object Based Image Analysis, structural features |
| Status : Conditional Accept (Poster) |
