基于改进帧间差分法与背景差分法车辆检测

运动车辆进行高效实时检测存在目标轮廓缺失、目标内部有空洞、背景无法实时更新等困难。基于此,提出了改进的三帧间差分法和帧间差分法、背景差分法融合算法,在应用改进三帧间差分法解决目标轮廓不完整、利用基于混合高斯模型建模的背景差分法实现目标背景的实时更新基础上,将两者融合,进行运动车辆检测。实验证明,所提出的算法可以较好地解决运动目标轮廓缺失以及背景无法实时更新的问题。

基于FPGA的动态目标检测与防御躲避系统设计

针对传统动态目标检测实时性差、功耗高及精度低等问题,提出了一种基于FPGA芯片的高精度、低功耗动态目标检测与防御躲避系统。该系统采集OV5640摄像头像素信息,经DDR4高速缓存后,依次对图像进行多步预处理,包括灰度化、自适应快速中值滤波、改进型三帧间差分、形态学运算及包围盒检测等,在HDMI液晶屏上实时显示目标检测结果。系统根据计算出的动态目标中心坐标,驱动电机控制摄像头进行精准的对角躲避。硬件测试结果表明,该系统在50 MHz的时钟频率下,视频帧率达到60 FPS,具有较高的实时性和鲁棒性,能够清晰并准确检测出动态目标,且防御躲避设计可行,功耗仅为0.969 W。

An improved Vibe algorithm for illumination mutations

The visual background extractor(Vibe)algorithm can lead to a large area of false detection in the extracted foreground target when the illumination is mutated.An improved Vibe method based on the YCbCr color space and improved three-frame difference is proposed in this paper.The algorithm detects the illumination mutation frames accurately based on the difference between the luminance components of two frames adjacent to a video frame.If there exists a foreground moving target in the previous frame of the mutated frame,three-frame difference method is utilized;otherwise,Vibe method using current frame is used to initialize background.Improved three-frame differential method based on the difference in brightness between two frames of the video changes the size of the threshold adaptively to reduce the interference of noise on the foreground extraction.Experiment results show that the improved Vibe algorithm can not only suppress the“ghost”phenomenon effectively but also improve the accuracy and completeness of target detection,as well as reduce error rate of detection when the illumination is mutated.

基于OpenCV的视频序列目标检测与跟踪技术研究

根据运动目标因速度时变性强,路径不确定等特点,提出一种基于三帧间差分与CAMShift相结合的目标检测与跟踪算法。该方法首先建立高斯背景模型,并对视频帧用三帧差分进行处理,检测出运动目标,然后利用Camshift算法对目标进行跟踪。实验结果表明,该方法计算量小,受环境变化影响小,目标检测准确性高。