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This paper presents a vehicle collision avoidance method and it is associated with the exploitation of multiple features based on the AdaBoost classifier result. The proposed system will enhance the precision rate and accuracy of vehicle detection from 72% to 96% using an AdaBoost detection method extracting multiple features in vehicle detection and false alarms are reduced.
This paper proposes a rear vision camera-based vehicle detection system which could detect if any rear vehicle exists in ego lane and if any vehicles in adjacent lanes are overtaking. The source image is firstly applied with distortion calibration which helps the following Hough transform to detect the existence of lane lines. The rear vehicle in ego lane is detected by a combination of feature-based...
This paper proposes a vision-based vehicle surveillance system for parking lot management in outdoor environments. Due to the limited field of view of camera, this system uses multiple cameras for monitoring a wide parking area. Then, an affine transformation is used for merging the scenes obtained from these multiple cameras. Two major components are included, i.e., vehicle counting and parking lot...
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