文件名称:csit2305
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This paper presents a novel approach for detecting vehicles for driver assistance. Assuming flat
roads, vanishing point is first estimated using Hough transform space to reduce the
computational complexity. Localization of vehicles is carried using horizontal projection on the
horizontal gradient image below vanishing point. An uppermost and lowermost peak in the
horizontal profile corresponds to search space of vehicles. Binarization of search space on the
horizontal gradient image is done using Otsu algorithm. Verification of vehicles is carried
through a series of rule based classifiers constructed using statistical moments, observing peaks
in vertical profiling, vehicle texture, symmetry and shadow property. Experimentation was
carried out on flat highway roads and detection rate of vehicles is nearly found to be 88.23 -This paper presents a novel approach for detecting vehicles for driver assistance. Assuming flat
roads, vanishing point is first estimated using Hough transform space to reduce the
computational complexity. Localization of vehicles is carried using horizontal projection on the
horizontal gradient image below vanishing point. An uppermost and lowermost peak in the
horizontal profile corresponds to search space of vehicles. Binarization of search space on the
horizontal gradient image is done using Otsu algorithm. Verification of vehicles is carried
through a series of rule based classifiers constructed using statistical moments, observing peaks
in vertical profiling, vehicle texture, symmetry and shadow property. Experimentation was
carried out on flat highway roads and detection rate of vehicles is nearly found to be 88.23
roads, vanishing point is first estimated using Hough transform space to reduce the
computational complexity. Localization of vehicles is carried using horizontal projection on the
horizontal gradient image below vanishing point. An uppermost and lowermost peak in the
horizontal profile corresponds to search space of vehicles. Binarization of search space on the
horizontal gradient image is done using Otsu algorithm. Verification of vehicles is carried
through a series of rule based classifiers constructed using statistical moments, observing peaks
in vertical profiling, vehicle texture, symmetry and shadow property. Experimentation was
carried out on flat highway roads and detection rate of vehicles is nearly found to be 88.23 -This paper presents a novel approach for detecting vehicles for driver assistance. Assuming flat
roads, vanishing point is first estimated using Hough transform space to reduce the
computational complexity. Localization of vehicles is carried using horizontal projection on the
horizontal gradient image below vanishing point. An uppermost and lowermost peak in the
horizontal profile corresponds to search space of vehicles. Binarization of search space on the
horizontal gradient image is done using Otsu algorithm. Verification of vehicles is carried
through a series of rule based classifiers constructed using statistical moments, observing peaks
in vertical profiling, vehicle texture, symmetry and shadow property. Experimentation was
carried out on flat highway roads and detection rate of vehicles is nearly found to be 88.23
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