Identification and feature extraction of moving vehicles in LabVIEW

Suresh Babu Changalasetty, Ahmed S. Badawy, Wade Ghribi, Lalitha Saroja Thota
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引用次数: 13

Abstract

In recent years, video monitoring and surveillance systems have been widely used in traffic management. The image sequences for traffic scenes are recorded by a stationary camera. The video clip is sent to LabVIEW program to convert into image frames. NI LabVIEW vision assistant module is used to detect the moving vehicle. The method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Background subtraction is used which improves the adaptive background mixture model and makes the system learn faster and more accurately, as well as adapt effectively to changing environments. The resulting system robustly identifies vehicles, rejecting background and tracks vehicles over a specific period of time. Once the (object) vehicle is tracked, the attributes of the vehicle like width, length, perimeter, area etc are extracted by image process feature extraction techniques. In proposed system we use LabVIEW and Vision assistant module for image processing and feature extraction. The project will benefit to reduce cost of traffic monitoring system and complete automation of traffic monitoring system.
LabVIEW中移动车辆的识别与特征提取
近年来,视频监控系统在交通管理中得到了广泛的应用。交通场景的图像序列由固定摄像机记录。将视频片段发送到LabVIEW程序中转换为图像帧。使用NI LabVIEW视觉辅助模块对移动车辆进行检测。该方法基于车辆在图像序列中移动时建立区域和车辆之间的对应关系。采用背景减法改进了自适应背景混合模型,使系统学习更快、更准确,并能有效地适应不断变化的环境。由此产生的系统可以可靠地识别车辆,拒绝背景信息,并在特定时间段内跟踪车辆。一旦目标车辆被跟踪,通过图像处理特征提取技术提取车辆的宽度、长度、周长、面积等属性。本系统采用LabVIEW和视觉辅助模块进行图像处理和特征提取。该项目有利于降低交通监控系统成本,实现交通监控系统的自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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