Vehicle Detection and Tracking Techniques Used in Moving Vehicles (original) (raw)
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Moving vehicle detection from video sequences for Traffic Surveillance System
Journal of Engineering and Technology for Industrial Applications, 2021
In the current scenario, Intelligent Transportation Systems play a significant role in smart city platform. Automatic moving vehicle detection from video sequences is the core component of the automated traffic management system. Humans can easily detect and recognize objects from complex scenes in a flash. Translating that thought process to a machine, however, requires us to learn the art of object detection using computer vision algorithms. This paper solves the traffic issues of the urban areas with an intelligent automatic transportation system. This paper includes automatic vehicle counting with the help of blob analysis, background subtraction with the use of a dynamic autoregressive moving average model, identify the moving objects with the help of a Boundary block detection algorithm, and tracking the vehicle. This paper analyses the procedure of a video-based traffic congestion system and divides it into greying, binarisation, de-nosing, and moving target detection. The in...
A background subtraction algorithm for detecting and tracking vehicles
Expert Systems With Applications, 2011
An innovative system for detecting and extracting vehicles in traffic surveillance scenes is presented. This system involves locating moving objects present in complex road scenes by implementing an advanced background subtraction methodology. The innovation concerns a histogram-based filtering procedure, which collects scatter background information carried in a series of frames, at pixel level, generating reliable instances of the actual background. The proposed algorithm reconstructs a background instance on demand under any traffic conditions. The background reconstruction algorithm demonstrated a rather robust performance in various operating conditions including unstable lighting, different view-angles and congestion.
Detecting and Tracking Moving Vehicles for Traffic Surveillance
2015
Traffic surveillance has become an important issue in traffic monitoring. In general, to observe the traffic flow, vision based traffic surveillance is one of the most popular methods. This paper presents an efficient method for detecting and tracking vehicles that aims to locate and segment interesting vehicle from a video with occlusions in traffic surveillance. Initially background subtraction is used for detecting moving vehicles from static cameras using frame differencing method. This method detects the foreground objects based on the difference between the reference frame and the original frame. Then the shadows in the foreground are eliminated by the edge extraction and the edge of the moving vehicle is detected. Finally the vehicle is detected using Histogram of Oriented Gradient (HOG) and Relative Discriminative Histogram of Oriented Gradient (RDHOG) method which represents the shape and magnitude of the vehicle and by generating trajectory of the moving vehicles. This met...
2020
Vehicle detection is an ultimate result of identifying the vehicle as objects and analysis the object parameter like position, total counts and individual speeds to infer the decisions about the smart transportation. There are lots of technology have been formed in the same fashion to detect vehicle on the real time road. Various BS techniques are used to prevail over the issues of illustration variation, shadows, background cutter and camouflage. In this study, a method of tracking and detecting the vehicles from the real time video steaming using a single camera on the road has proposed in which the blob tracker algorithm is used with background subtraction (BS)process to achieve a real high-performance system. The proposed method has real time potentiality and any additional sensor input is not needed to perform this operation. The system's operation is performed on huge number of still images of vehicles and multiple video scenes in terms of completeness, correctness and ove...
Moving Vehicle Identification Using Background Registration Technique for Traffic Surveillance
…, 2009
Real-time segmentation of moving regions in image sequences is a fundamental step in many vision systems including automated visual surveillance and human-machine interface. In this paper we present a framework for detecting some important but unknown knowledge like vehicle identification and traffic flow count. The objective is to monitor activities at traffic intersections for detecting congestions, and then predict the traffic flow which assists in regulating traffic. The present algorithm for vision-based detection and counting of vehicles in monocular image sequences for traffic scenes are recorded by a stationary camera. 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 at intersection, rejecting background and tracks vehicles over a specific period of time. Real-life traffic video sequences are used to illustrate the effectiveness of the proposed algorithm.
Moving Object Tracking of Vehicle Detection": A Concise Review
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vehicle detection and tracking applications play an important role for military and civilian applications such as in highway traffic surveillance control management and traffic planning.This paper presents a review on the various techniques of On-Road Vehicle detection systems that are based on motion model. In this paper a literature Survey of previous and recent works is presented on visionbased vehicle detection using sensors. Detecting the objects in the video and tracking their motion to identify their characteristics has been emerging as a demanding research area in the domain of Image Processing and Computer Vision. The traffic image analysis comprises of three parts: (1) Traffic Analysis (2) Motion Vehicle Detection and Segmentation Approaches and (3) Vehicle Tracking Approaches. In this survey, we have classified these methods into various groups, and these groups are providing a detailed description of various representation methods and find out their positive and negative aspects.
Review on Image Processing Based Vehicle Detection & Tracking System
The difficulty of obtaining the initial background there is the inaccuracy of real-time background update and the difficulty of controlling the update speed in moving vehicle detection of traffic video. The project aim proposes an accurate and effective moving vehicle detection method which can be used in complex traffic environment. Vehicle detection and tracking system plays an important role for civilian and military applications such as in highway traffic surveillance control, management and urban traffic planning. Vehicle detection process on road are used for vehicle tracking, counts the vehicle, average speed of each individual vehicle, traffic analysis and vehicle categorizing objectives and may be implemented under different environments changes. In this review, we present a concise overview of image processing methods and analysis tools which used in building these previous mentioned applications that involved developing traffic surveillance systems. More precisely and in contrast with other reviews, we classified the processing methods under three categories for more clarification to explain the traffic system.
A NOVEL DETECTION AND TRACKING ALGORITHM FOR TRAFFIC SURVEILLANCE SYSTEM
Vehicle detection and tracking place a vital role in traffic surveillance system (TSS). In the past, many methods had been introduced and implemented still a challenging issue because of dynamic textures such as rain fall, snow and absence of light. Therefore to overcome these problems introduce a novel tracking algorithm based on background subtraction and morphological operations. Firstly the background method is used to detect the moving objects from the video and then morphological operations are applied to remove the noise regions and obtaining more accurate segmentation results. After vehicle detection, a object-based vehicle tracking method is used for building the correspondence between vehicles detected at different time instants. After vehicle tracking, calculate the vehicle count from video.
Performance comparison of Background Estimation algorithms for detecting moving vehicle
Background subtraction is the one of the crucial step in detecting the moving object. Many techniques were proposed for detected moving object however there are few comparative studies carried out to verify their performance. In this paper a performance comparison of different background subtraction algorithms is carried out from the literature as well as through implementation. We investigate some of the techniques which varying from simple techniques such as frame differencing and approximation median filter, to more complicated probabilistic modeling techniques. Our results show that simple techniques such as approximation median filter can produce good results with much lower computational complexity.
Vehicle Detection and Speed Tracking
International journal of engineering research and technology, 2021
Speed detection of vehicle and its tracking plays an important role for safety of civilian lives, thus preventing many mishaps. This module plays a very significant role in the monitoring of traffic where efficient management and safety of citizens is the main concern. In this paper, we discuss about potential methods for detecting vehicle and its speed. Various research has already been conducted and various papers have also been published in this area. The proposed method consists of mainly three steps background subtraction, feature extraction and vehicle tracking. The speed is determined using distance travelled by vehicle over number of frames and frame rate. For vehicle detection, we use various techniques and algorithms like Background Subtraction Method, Feature Based Method, Frame Differencing and motion-based method, Gaussian mixture model and Blob Detection algorithm. Vehicle detection is a part of speed detection where, the vehicle is located using various algorithms and later determination of speed takes place. The process for speed detection is as follows:1) Input Video 2)Pre-Processing 3)Moving Vehicle detection 4)Feature Extraction 5)Vehicle tracking 6)Speed detection. Many accidents and mishaps can be avoided if vehicle detection and speed tracking techniques are implemented.