【作者】 王静；

【导师】 保文星；

【作者基本信息】 北方民族大学 ， 计算机应用技术， 2009， 硕士

【摘要】 随着数字图像处理技术和计算机视觉技术的发展,视频检测技术逐渐成为智能交通系统中求取车辆速度等交通参数的重要方法,得到越来越多人的重视和肯定。准确交通信息的获取是智能交通系统及其子系统实现其各项功能的基础,所以利用视频检测技术来检测运动车辆目标、采集车速等实时交通参数成为当前智能交通系统研究与开发的重点之一。本文根据从城市交通道路上采集的交通视频序列,参考视频检测方面现有的研究成果,提出两种运动目标检测方法,并通过对检测到的目标进行定位和跟踪,实现了车辆速度测量。论文主要工作包括:1、本文针对智能交通系统中的交通视频序列,在现有的运动目标检测技术的基础上,提出了一种基于帧间差分法、图像阈值分割和数学形态学的运动目标检测方法。并对该方法的内容和实现过程进行了详细的说明。2、本文研究了基于图像分割的目标分割方法。结合智能优化算法—人工免疫系统和遗传算法,本文提出一种改进的遗传算法—克隆选择遗传算法。该算法将克隆选择代替遗传算法中的概率选择,避免了改进后的遗传算法出现早熟收敛现象。仿真实验证明,基于克隆选择遗传算法的图像阈值分割对处理不同类型的图像具有良好的分割效果和较强的适应能力,也进一步验证了克隆选择遗传算法的有效性和实用性。3、本文采用一种亚像素定位技术—灰度重心法对运动目标进行定位,并通过匹配连续两帧中同一车辆目标的最小外接矩形来实现目标跟踪。最后,利用不同帧的车辆自身长度的比例系数来得到车辆的行驶距离,计算车速。4、在Matlab仿真实验环境下,建立了视频检测系统的实验平台,编程实现了运动目标检测过程,以及运动车辆速度的测量。仿真实验验证了本文所提方法的正确性和有效性。更多还原

【Abstract】 With the development of digital image processing technology and computer vision technology, video detection technology becomes an important method to obtain traffic parameters such as vehicle speed in the Intelligent Transport System, and gains regard and affirmation by more and more people. To obtain exact traffic information is the foundation of carrying out all functions in the Intelligent Transport System and its subsystems, therefore, using video detection technology to detect moving vehicle objects、collect real-time traffic parameters such as vehicle speed becomes one of emphases in the research and exploiture of the Intelligent Transport System currently.According to the traffic video sequence which collected from city traffic road, consulting study works in video detection, this paper proposed two kinds of moving objects detection methods, and implemented vehicle speed measurement after locating and tracking the detected objects. The major work implemented in this paper is presented as follows:1、Based on current moving objects detection technology, this paper proposed a moving objects detection method based on difference in frames、image threshold segmentation and mathematical morphology, which is aimed at traffic video sequence in the Intelligent Transport System. Besides, the content and procession of this method are illuminated in detail.2、This paper studied object segmentation method which is based on image segmentation. Combined with intelligent optimization algorithms—Artificial Immune System(AIS) and Genetic Algorithm(GA), this paper proposed an improved Genetic Algorithm called Clonal Selection Genetic Algorithm(CSGA). To avoid the improved Genetic Algorithm appearing premature convergence, this algorithm replaced probability selection in Genetic Algorithm by clonal selection. Emulational experimental results show that, image threshold segmentation based on CSGA has good segmentation effects and strong flexibility,as well as its validity and practicability.3、This paper adopted a kind of subpixel location technologies—gravity method of the gray scale for locating moving objects, and through matching the smallest enclosing rectangle of same vehicle object in two consecutive frames to implement objects tracking. finally, vehicle length proportion coefficient in different frames was used to obtain vehicle moving distance and calculate speed.4、Under the Matlab environment, experiment platform of video detection system was established, moving objects detection processing was implemented, as well as moving vehicle speed measurement. Emulational experimental results showed exactness and validity of the methods mentioned in this paper.更多还原