標題: | A New Approach to Video-Based Traffic Surveillance Using Fuzzy Hybrid Information Inference Mechanism |
作者: | Wu, Bing-Fei Kao, Chih-Chung Juang, Jhy-Hong Huang, Yi-Shiun 電控工程研究所 Institute of Electrical and Control Engineering |
關鍵字: | Congested condition;traffic surveillance;vehicle detection;vehicle tracking |
公開日期: | 1-三月-2013 |
摘要: | This study proposes a new approach to video-based traffic surveillance using a fuzzy hybrid information inference mechanism (FHIIM). The three major contributions of the proposed approach are background updating, vehicle detection with block-based segmentation, and vehicle tracking with error compensation. During background updating, small-range updating is adopted to overcome environmental changes under congested conditions. During vehicle detection, the proposed approach detects the vehicle candidates from the foreground image, and it resolves problems such as headlight effects. The tracking technique is employed to track vehicles in consecutive frames. First, the method detects edge features in congested scenes. Next, FHIIM is employed to determine the tracked vehicles. Finally, a method that compensates for error cases under congested conditions is applied to refine the tracking qualities. In our experiments, we tested scenarios both inside and outside the tunnel with three lanes. The results showed that the proposed system exhibits good performance under congested conditions. |
URI: | http://dx.doi.org/10.1109/TITS.2012.2208190 http://hdl.handle.net/11536/22414 |
ISSN: | 1524-9050 |
DOI: | 10.1109/TITS.2012.2208190 |
期刊: | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS |
Volume: | 14 |
Issue: | 1 |
起始頁: | 485 |
結束頁: | 491 |
顯示於類別: | 期刊論文 |