Digital Image Processing
Cascade of classifiers for vehicle detection
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Computers & Mathematics with Applications
Degradation of turbid images based on the adaptive logarithmic algorithm
Computers & Mathematics with Applications
Fast pedestrian detection system with a two layer cascade of classifiers
Computers & Mathematics with Applications
Gait detection based stable locomotion control system for biped robots
Computers & Mathematics with Applications
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On the basis of a cost-effective embedded system, this work implements a preceding vehicle detection system by using computer vision technologies. The road scenes are acquired with a monocular camera. The features of the vehicle in front are extracted and recognized by the proposed refined image processing algorithm, and a tracking process based on optical flow is also applied for reducing the complexity of computing. The system also provides the longitudinal distance information for the further function of adaptive cruise control. Moreover, voice alerts and image recording will be activated if the distance is less than the safe range. A statistical base of 100 video road images are tested in our experiments; the natures of the vehicles include sedan, minivan, truck, and bus. The experimental results show that the proportion of correct identifications of proceeding vehicles is above 95.8%, testing on highways in the daytime. Experimental results also indicate that the system correctly identifies vehicles in real time.