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In a visual driver-assistance system, vehicle detection is one of the major tasks. This paper presents a vehicle detection method based on multi-features fusion in the images acquired by a fisheye camera. The vehicle detection algorithm can be divided into three main steps: fisheye image calibration, generation of candidates with respect to a vehicle and verification of the candidates. In the fist...
It is a difficult problem that targets are detected in nature background, especially in images corrupted by noise. In order to solve this problem, a method based on feature salience is proposed for targets automatic detection in nature background. Firstly, an adaptive wavelet thresholding method is used to denoise for noisy target images. Then minimum probability of error was been used to build to...
The paper presents a method for locating vehicle license plates using feature salience fusions. Feature salience is used to select target features based on minimum probability of error. In order to fuse these salient features, the Dempster-Shafer evidence theory is used. Finally, this method gives the final location of the license plates. The method offers robustness when dealing with noisy. Experimental...
This paper presents a road signs detection, recognition and tracking system based on multi-cues hybrid. In detection stage, the color and gradient cues are used to segment the interesting regions, and the corner and geometrical cues are used to detect the signs. A pseudo RGB-HSI conversion method without the need of nonlinear transformation is presented for color extraction. In recognition stage,...
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