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- 完成车辆计数功能，视频中有一个车辆通过检测带就有计数就加1。-Complete the vehicle counting function, the video has a vehicle count by testing with have to add 1.
video-vehicle-detection
- 用于视频车辆检测，使用matlab语音，测试结果准确率达90 -For video vehicle detection, the use of matlab voice, test results are accurate 90
VehicleCounter
- VC++下编写的基于视频的交通路况检测系统，实现了流量、车速、车型检测等功能-Prepared under the VC++ video-based detection system for traffic and road conditions to achieve the flow, speed, vehicle detection,
LPR-mobile
- 视频车辆牌照识别，包含汉字处理算法，BP神经网络设计。识别率高达90％以上。-Video vehicle license plate recognition, including the Chinese characters processing algorithms, BP neural network design. Recognition rate as high as 90 .
OpencvTest
- 微扑翼飞行器(FMAV)是一种模仿鸟类或昆虫飞行的新概念飞行器，根据拍摄的视频图像，按照计算机视觉理论设定了适用于微扑翼飞行器的运动模态检测方案。VC++6.0平台上进行了编程实现。经过试验可以看出这种模态检测方法的可行性和准确性，其结果对微扑翼飞行器的优化改进起到了积极的作用。 -Flapping-wing aircraft (FMAV) is a kind of mimic the flight of birds or insects of a new concept vehicle,
Tracking_and_classifying_moving_objects_from_video
- Q. Zhou, J.K. Aggarwal. Tracking and Classifying Moving Objects from Video. 这篇文章另辟蹊径，利用“紧凑度值的变化、运动方向的变化”，区分人、人群、机动车。达到良好的分类效果。是运动目标分类领域的好文章。-Q. Zhou, JK Aggarwal. Tracking and Classifying Moving Objects from Video. This article open a new path, by us
Object_Classification_and_Tracking_in_Video_Survei
- Zang, Q. and Klette, R. Object Classification and Tracking in Video Surveillance. 这篇文章是有关多运动目标分类的文章。使用常用的长宽比作为分类特征，结合角点特征。提高了人车的分类效果。-Zang, Q. and Klette, R. Object Classification and Tracking in Video Surveillance. This article is about the many obj
TheResearchforRecognition
- 基于视频图像的运动车辆识别系统主要是由汽车牌照识别和汽车类型识 别两大核心技术构成，它在智能交通领域中有着广泛的应用，同时也是计算机 视觉、图像处理和模式识别等交叉学科研究的热门课题，因此对相关技术的研 究正受到普遍关注。本文正是在这一背景下，对运动车辆识别技术进行了系统 的研究。在车牌识别技术中，本文着重对车牌定位和车牌字符识别等关键技术 所涉及的难点进行了深入的研究。在车型识别技术中，与当前国内外学者侧重 于研究车辆外形、大小的识别不同，本文主要侧重对汽车标志的定位和
object-detect
- 改程序能够读取视频文件并且可以检测到运动的物体，配置好opencv后可以直接运行，本程序以车辆监控为例子，所以可以用于智能监控-Reform program that can read video files and can detect movement of objects can be configured directly opencv run, the procedure for vehicle monitoring, for example, it can be used for i
MultipleVehicleDetectionandTrackinginHardRealTime.
- 这个是在IEEE上下载的一篇英文文献，基于视频图像的多目标车辆的检测跟踪，对毕业设计有帮助-This is an IEEE downloaded in English literature, based on video images of the detection of multi-objective vehicle tracking, designed to help graduate
Video-Frame
- 视频帧分析源码，用于车辆检测及车牌识别，采用背景差分法-Analysis of source video frame for vehicle license plate detection and identification, using the background difference method
LicensePlateLocation
- 车牌定位VC++源程序，高速公路视频抓拍汽车车牌并分析车牌号。-License plate location VC++ source code, highway video capture and analyze vehicle license plate number plate.
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- Review on Vehicle Detection Based on Video for Traffic Surveillance
videoldws
- 本程序在视频流中检测道路线标记，并强调该车辆的行驶线。这些信息可以被用来检测车辆的意外离开并发出警告。-This demo detects road lane markers in a video stream and highlights the lane in which the vehicle is driven. This information can be used to detect an unintended departure from the lane and issu
VideoBasedVehicleDetectionAndTrackingTechniques.ra
- 基于交通监控视频的车辆检测与跟踪算法的研究-Based traffic surveillance video vehicle detection and tracking algorithm
Speed_identification_method_based_on_video
- 基于视频的车速鉴定方法,介绍通过检测视频来识别车辆，计算车辆速度-Speed identification method based on video to introduce the video to identify the vehicle by detecting the calculated vehicle speed
CarCount
- 该代码实现车辆的检测，采用了训练的方式，从视频中提取背景，然后做差分，连通域提取等步骤得道前景。该代码采用OPENCV实现。-The code to achieve vehicle detection, using training methods to extract from the video background, and then do differential, connected components extraction and other steps to attain the
singalframe
- 车辆视频检测，采用高斯背景更新方法，基于OPENCV的图像视频检测算法-Vehicle video detection, the Gaussian background updating method, based on video image detection algorithm OPENCV
An-improved-video-based-vehicle-detection-and-iden
- 一种改进的基于视频的车辆检测与识别方法An improved video-based vehicle detection and identification-An improved video-based vehicle detection and identification
chepaidingweisuanfayanjiu
- 摘要 车辆牌照识别(License Plate Recognition System, LPR)作为目标自动识别的一 种重要形式，可用于电子收费、出入控制、车流监控等众多场合，从而提高交通 管理自动化的程度，它的相关技术的研究正逐渐受到人们的重视。 本文主要介绍基于Run Length原理和Tamura纹理的车牌定位系统，该系统是基 于视频流进行开发的，主要包括车辆运动区域检测、车牌图像处理、车牌定位。 其中车辆运动区域检测利用多帧求平均的背景估计方法实现；车牌图像处理包