In order to decrease vehicle crashes, a new rear view vehicle detection system based on monocular vision is designed. First, a small and flexible hardware platform based on a DM642 digtal signal processor （DSP） micr...In order to decrease vehicle crashes, a new rear view vehicle detection system based on monocular vision is designed. First, a small and flexible hardware platform based on a DM642 digtal signal processor （DSP） micro-controller is built. Then, a two-step vehicle detection algorithm is proposed. In the first step, a fast vehicle edge and symmetry fusion algorithm is used and a low threshold is set so that all the possible vehicles have a nearly 100% detection rate （TP） and the non-vehicles have a high false detection rate （FP）, i. e., all the possible vehicles can be obtained. In the second step, a classifier using a probabilistic neural network （PNN） which is based on multiple scales and an orientation Gabor feature is trained to classify the possible vehicles and eliminate the false detected vehicles from the candidate vehicles generated in the first step. Experimental results demonstrate that the proposed system maintains a high detection rate and a low false detection rate under different road, weather and lighting conditions.展开更多
提出基因重要度的概念,通过实验证明基因重要度对于单变量边缘分布算法(Unvaried Marginal Distribution Algo-rithm,UMDA)收敛的重要性.由此提出一种基于基因重要度的进化算法.该算法首先对组成染色体的各基因进行重要度排序,随后对重...提出基因重要度的概念,通过实验证明基因重要度对于单变量边缘分布算法(Unvaried Marginal Distribution Algo-rithm,UMDA)收敛的重要性.由此提出一种基于基因重要度的进化算法.该算法首先对组成染色体的各基因进行重要度排序,随后对重要度大的基因先进行收敛操作,每次收敛当前重要度最大的基因,直到所有基因全部收敛.实验数据表明,本算法的收敛速度更快,而且更容易求出满意解.展开更多
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(2009BAG13A04)Jiangsu Transportation Science Research Program(No.08X09)Program of Suzhou Science and Technology(No.SG201076)
文摘In order to decrease vehicle crashes, a new rear view vehicle detection system based on monocular vision is designed. First, a small and flexible hardware platform based on a DM642 digtal signal processor （DSP） micro-controller is built. Then, a two-step vehicle detection algorithm is proposed. In the first step, a fast vehicle edge and symmetry fusion algorithm is used and a low threshold is set so that all the possible vehicles have a nearly 100% detection rate （TP） and the non-vehicles have a high false detection rate （FP）, i. e., all the possible vehicles can be obtained. In the second step, a classifier using a probabilistic neural network （PNN） which is based on multiple scales and an orientation Gabor feature is trained to classify the possible vehicles and eliminate the false detected vehicles from the candidate vehicles generated in the first step. Experimental results demonstrate that the proposed system maintains a high detection rate and a low false detection rate under different road, weather and lighting conditions.
文摘提出基因重要度的概念,通过实验证明基因重要度对于单变量边缘分布算法(Unvaried Marginal Distribution Algo-rithm,UMDA)收敛的重要性.由此提出一种基于基因重要度的进化算法.该算法首先对组成染色体的各基因进行重要度排序,随后对重要度大的基因先进行收敛操作,每次收敛当前重要度最大的基因,直到所有基因全部收敛.实验数据表明,本算法的收敛速度更快,而且更容易求出满意解.
