【作者】 乔世坤；

【导师】 焦淑红；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2007， 硕士

【摘要】 运动目标检测已成为图像处理技术与计算机视觉领域中的一个重要课题，运动目标检测多是基于底层视频信息的检测，由于大多数图像处理过程中考虑的是对应运动区域的像素，所以运动区域的有效提取对于目标分类、目标跟踪以及行为理解等工作具有重要的意义。运动目标检测有极其广泛的应用范围，比如：军事侦察、智能监控和交通检测等领域。用于运动目标检测的序列图像可分为静止背景、运动背景两种情况，本文是基于静止背景的研究。文中首先概要介绍了运动目标检测的几种常用方法，包括光流法、帧间差分法、背景消减法，对各种方法进行了比较，并分析了其优缺点。在此基础上本文提出一种静止背景中基于边界的运动目标检测算法，本算法首先计算相邻两帧图像差分图像的阈值，将差分图像转化为二值图像，然后对二值图像进行形态学滤波确定运动目标的粗略位置，同时对当前帧进行边缘检测，将此边缘检测结果与前者确定的运动目标粗略位置进行交运算，得到运动目标的边界，再经滤波、区域填充等处理，最终获得运动目标的区域。实验表明，本算法相对于传统的帧间差分法对运动目标速度要求低，较好的克服了其不能准确检测运动目标大小的问题，保持其对背景渐变不敏感的优点，本算法检测有效、稳定，无论单目标检测还是多目标检测，均取得了较好的效果。更多还原

【Abstract】 Moving objects detection is one of the most important issues in image processing and computer vision. It belongs to bottom video information detection. Valid acquiring of moving region is important in object classifying, object tracking and behavior understanding because the pixels of the moving region are processed mainly. It is used widely in many fields, such as military reconnaissance, video surveillance and monitoring, traffic detection. Image sequences in moving objects detection can be divided into two types by which background is static or moving. The thesis is based on static background.First, some common approaches in the field of detecting moving objects are introduced, including optical flow method, two consecutive frame subtraction method and background modeling method. Their advantages and disadvantages are compared and pointed out in this thesis. Then, an edge-based moving object detection algorithm is proposed. In the algorithm, the threshold of the difference images is calculated from the two consecutive frame images. Then the rough position of the moving object is decided by using morphological filter for binary image. Edge detection is carried for the current frame at the same time. For getting the edge of the moving object, the "and" operation is done between the results of rough position and the edge detection. At last, the area of the moving object is obtained through filtering and region filling.Compared with traditional two consecutive from subtraction method, It solves the problem of not exactly detecting the size of moving objects, keeps the advantages of not sensitive for gradual changing background for the detection. The algorithm is valid, steady in object detection. It has obtained a better effect for not only single object detection but also multi-moving objects detection.更多还原