针对视觉背景提取(visual background extractor,ViBe)算法在运动目标检测过程中容易受到噪声干扰的问题,将两帧差分法融入ViBe的前景检测阶段,提出一种融合两帧差分信息的改进ViBe算法(ViBe with two-frame differencing,ViBe-TD)。首...针对视觉背景提取(visual background extractor,ViBe)算法在运动目标检测过程中容易受到噪声干扰的问题,将两帧差分法融入ViBe的前景检测阶段,提出一种融合两帧差分信息的改进ViBe算法(ViBe with two-frame differencing,ViBe-TD)。首先,设计单阈值形ViBe(single-threshold form of ViBe,S-ViBe)检测,为信息融合做准备;其次,基于逻辑斯蒂(logistic)回归模型,实现像素点上两帧差分和S-ViBe检测信息的融合;最后,综合两类检测信息完成前景像素点的判定。实验结果表明,ViBe-TD算法在4种不同场景视频上的检测效果达到了0.932的平均精确率,0.785的平均召回率以及0.842的平均F 1值。与原算法相比,ViBe-TD算法的各项指标平均有0.158的提高,具有良好的检测效果。展开更多
Setting up a pair of moving frames on the two pitch circles, the instantaneous contact point being considered the attendant point of the frames, the equation of the trace of the contact points in the frame being p = p...Setting up a pair of moving frames on the two pitch circles, the instantaneous contact point being considered the attendant point of the frames, the equation of the trace of the contact points in the frame being p = p(t~), we can deduce that the basic rule for the gear profiles is dp / ds = - csos 0 where s is the are length of the pitch circles. Giving a known function of p = p (0), we can obtain the equations of the two conjugate gear profiles and the curvatures and inductive curvature of the profiles. The second order contact phenomenon that a given gear profile can contact with the mating gear at two points simultaneously is discussed by the method of moving frames.展开更多
A novel frame shift and integral technique for the enhancement of low light level moving image sequence is introduced. According to the technique, motion parameters of target are measured by algorithm based on differe...A novel frame shift and integral technique for the enhancement of low light level moving image sequence is introduced. According to the technique, motion parameters of target are measured by algorithm based on difference processing. To obtain spatial relativity, images are shifted according to the motion parameters. As a result, the processing of integral and average can be applied to images that have been shifted. The technique of frame shift and integral that includes the algorithm of motion parameter determination is discussed, experiments with low light level moving image sequences are also described. The experiment results show the effectiveness and the robustness of the parameter determination algorithm, and the improvement in the signal-to-noise ratio （SNR） of low light level moving images.展开更多
文摘针对视觉背景提取(visual background extractor,ViBe)算法在运动目标检测过程中容易受到噪声干扰的问题,将两帧差分法融入ViBe的前景检测阶段,提出一种融合两帧差分信息的改进ViBe算法(ViBe with two-frame differencing,ViBe-TD)。首先,设计单阈值形ViBe(single-threshold form of ViBe,S-ViBe)检测,为信息融合做准备;其次,基于逻辑斯蒂(logistic)回归模型,实现像素点上两帧差分和S-ViBe检测信息的融合;最后,综合两类检测信息完成前景像素点的判定。实验结果表明,ViBe-TD算法在4种不同场景视频上的检测效果达到了0.932的平均精确率,0.785的平均召回率以及0.842的平均F 1值。与原算法相比,ViBe-TD算法的各项指标平均有0.158的提高,具有良好的检测效果。
文摘Setting up a pair of moving frames on the two pitch circles, the instantaneous contact point being considered the attendant point of the frames, the equation of the trace of the contact points in the frame being p = p(t~), we can deduce that the basic rule for the gear profiles is dp / ds = - csos 0 where s is the are length of the pitch circles. Giving a known function of p = p (0), we can obtain the equations of the two conjugate gear profiles and the curvatures and inductive curvature of the profiles. The second order contact phenomenon that a given gear profile can contact with the mating gear at two points simultaneously is discussed by the method of moving frames.
文摘A novel frame shift and integral technique for the enhancement of low light level moving image sequence is introduced. According to the technique, motion parameters of target are measured by algorithm based on difference processing. To obtain spatial relativity, images are shifted according to the motion parameters. As a result, the processing of integral and average can be applied to images that have been shifted. The technique of frame shift and integral that includes the algorithm of motion parameter determination is discussed, experiments with low light level moving image sequences are also described. The experiment results show the effectiveness and the robustness of the parameter determination algorithm, and the improvement in the signal-to-noise ratio （SNR） of low light level moving images.
