Title :
Vehicle detection and segmentation in dynamic traffic image sequences with scale-rate
Author_Institution :
HIEST Univ., Athens, Greece
Abstract :
The scale-rate of digital signals is presented to extract local complexity feature. It is proved experimentally that the scale-rate value has direct relationship with signals´ local changing rate. Based on the scale-rate, a new method of vehicle detection and segmentation is proposed for dynamic traffic image sequences. The experimental results show the effectiveness and efficiency of the vehicle segmentation method with scale-rate, which has better performance than the frame differencing method and the optical flow method.
Keywords :
digital signals; feature extraction; image segmentation; image sequences; object detection; road traffic; digital signals; dynamic traffic image sequences; frame differencing method; local complexity feature extraction; optical flow method; scale rate value; signals local changing rate; vehicle detection; vehicle segmentation; Feature extraction; Fractals; Image motion analysis; Image processing; Image segmentation; Image sequences; Optical sensors; Vehicle detection; Vehicle dynamics; Vehicles;
Conference_Titel :
Intelligent Transportation Systems, 2004. Proceedings. The 7th International IEEE Conference on
Print_ISBN :
0-7803-8500-4
DOI :
10.1109/ITSC.2004.1398963
