运动车辆检测水平集提取的研究

【作者】 杨莉；

【导师】 张荣国； 胡静；

【作者基本信息】 太原科技大学 ， 计算机应用技术， 2012， 硕士

【摘要】 运动目标的检测、提取及流量统计是计算机图像领域研究的重点，有着非常重要的应用价值。作为该领域最值得研究的内容之一，图像处理技术是实现运动目标检测及流量统计的一种有效方法，引起了各国研究人员的广泛关注。本文对常见运动目标检测的方法进行了分析，针对传统帧间差分法在光照、天气变化明显时的不适应性，提出了一种基于C-V模型的运动目标水平集提取新方法：首先，对运动区域进行初始检测，在对帧间差分法进行改进的基础上通过相邻视频帧的相减，选用自适应阈值判断出当前视频帧中的运动目标像素；其次，将检测出的运动目标区域经形态学处理后通过定义最小化能量函数构建运动目标轮廓提取的水平集C-V模型，实现运动目标轮廓的提取。实验结果表明，该方法的边缘准确率和检出率更高，能够更有效地提取运动目标。在利用上述方法检测到运动车辆的基础上，对多车道虚拟检测线车流量统计的方法进行了改进。它使用单条虚拟检测线技术实现了多车道情况下的车流量统计，能有效改善跨道行驶的车流量统计问题。作为实验验证，开发了一个车流量统计系统，该系统分为4个模块：视频载入模块、虚拟检测线设置模块、视频控制模块、车流量统计模块。实验结果表明，本文所提方法具有很好的实时性，识别率较高。更多还原

【Abstract】 Motion object detection, extraction and traffic flow statistics is a hotresearch in image domain of computer, and has very important applicationvalues. As the most worthy of study content, image processing technology isthe realization of motion detection and flow statistics is an effective method,it has aroused the extensive attention of researchers.In this paper, the common methods of target detection are analyzed, amotion object extraction algorithm based on level set C-V model is proposedin view of the traditional frame difference method in light, weather changesapparent inelasticity: firstly, on the moving area in initial detection, framedifference algorithm was improved and adjacent moving object pixels incurrent image were detected through adaptive threshold and adjacent videoframe subtracting technique. The proposed approach can improve the changeof light and weather effective; secondly, Construct and realize the level setC-V model of extracting the moving object contour though being processedby morphology after motion object detection. Experimental results show thatthe proposed approach for extracting moving object, which edge anddetecting accuracy rate is more powerful and can effectively extract themoving object.Based on the above method to detect moving vehicles, multi-lane testline traffic flow statistics method was improved. It uses a single virtualdetection line technology to realize traffic flow statistics of multi lane, andimprove the cross road traffic flow statistics effectively. As an experiment,develop a traffic flow statistics system, this system divided into four modules,which are video load module, virtual detecting line set module, video controlmodule, traffic flow statistics module. Experimental results show that theproposed method has the following characteristics: the real-time property andhigh recognize rate.更多还原