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This study presents an effective system for detecting and tracking moving vehicles in nighttime traffic scene for traffic surveillance. The proposed method identifies vehicles based on detecting and locating vehicle headlights and taillights by using the techniques of image segmentation and pattern analysis. First, to effectively extract bright objects of interest, a fast bright-object segmentation...
The automatic lane marking detection, vehicle detection and incident detection systems are proposed in this paper. The block-based background extraction that combines statistical algorithm and the moving block information is used to obtain the color background image more exactly. The lane detection algorithm is applied to obtain the lane information from the color background image without the limitation...
In this paper, the lane and vehicle detection with distance estimation algorithm is proposed by using a CCD camera mounted behind the windshield of our experimental car, TAIWAN iTS-1. The gray level and gradient value are applied for the lane marking detection. The lane marking information is utilized in vehicle detection algorithm. The front vehicles are recognized by comparing the gray level value...
In this paper, we work mainly on character recognition. First, we decompose the plate characters by framelet and select the transform coefficients using wrapper method as the character features, then send them to BP neural network for recognition. With our method, the recognition rate of letter characters reaches 99.25%, the number characters reaches 99.3%, the results illustrate that our method is...
The well-known vehicle detectors utilize the background extraction methods to segment the moving objects. The background updating concept is applied to overcome the luminance variation which results in the error detection. These systems will meet a challenge when detecting the vehicles in the traffic jam conditions at sunset. The vehicles will cover the road surface so that the background information...
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