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V-DaT: A Robust method for Vehicle Detection and Tracking

Latha Anuj , Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
Still, many challenging problems remain unsolved, such as addressing vehicle occlusions and reducing false detection. In this work, a method for vehicle detection and tracking is proposed.  ...  multi-directional filtering and fusion based background subtraction, thresholding, directional filtering and morphological operations for moving vehicle detection.  ...  [14] developed a robust multilane detection and tracking method where they used in-vehicle mono-camera and a forward-looking LIDAR technique.  ... 
doi:10.17762/turcomat.v12i2.2092 fatcat:o6okrw56ovcnjdwcdhcopxkcsu

Study on Stereo Vision-based Cross-country Obstacle Detection Technology for Intelligent Vehicle

Linhui Li, Rongben Wang, Mingheng Zhang
2007 Third International Conference on Natural Computation (ICNC 2007)  
The original images are preprocessed by Gaussian filter and contrast-limited adaptive histogram equalization (CLAHE) method to weaken the effect of noise, light and contrast.  ...  Cross-country intelligent vehicles always work in complicated environments with varying illuminations.  ...  Introduction Cross-country obstacle detection is one of the main components of intelligent vehicle guidance.  ... 
doi:10.1109/icnc.2007.693 dblp:conf/icnc/LiWZ07 fatcat:p2kpam7gq5avrfklxgu6foedoe

A Review On Lane Detection And Tracking Techniques

Pravin T. Mandlik, Prof A.B.Deshmukh
2016 Zenodo  
The main goal of these systems is to detect the lane stripes and to warn the driver in case of the vehicle tend to depart from the lane.  ...  Many intelligent vehicles transport systems have the lane detection system as an important element while driving. Therefore,Lane detection and tracking is the challenging task in computer vision.  ...  In presence of stop lines at cross walks, nearby vehicles detection not proper C.  ... 
doi:10.5281/zenodo.1466247 fatcat:fnrya3lzxnaohdutft6yklqwqu

A Survey on Vehicle Detection based on Vision

Surender Dhanaekaran, Karthi Ramachandran, Selvamuthukumar M, Nithya Velam, Soma Pal
2015 Modern Applied Science  
Many approaches use differe</span><span lang="EN-GB">nt types of information such as shadow, edge, light, to detect the vehicles. Here vision based vehicle detection techniques were summarized.  ...  Following topics discussed below, camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime  ...  In [7], SURF: Speeded up Robust Features and edges were combined to detect vehicles in the blind spot.  ... 
doi:10.5539/mas.v9n12p118 fatcat:2wasqlhgaje7ra2w6fdah6m3oy

A Lane Centerline Recognition System Based on Improved High Efficiency Hough transform

Tao Peng, YoungMin Jang, ByeongWoo Kim
2020 International journal of engineering research and technology  
Lane detection is a vital part of the intelligent vehicle detection system.  ...  In this paper, to improve the lane recognition rate more than the conventional method, we preprocess the collected images first, include image grayscale, Sobel operator edge detection and binarization  ...  ACKNOWLEDGEMENTS This work was supported by Korea Hydro & Nuclear Power company through the project "Nuclear Innovation Center for Haeoleum Alliance" and "Industrial technology infrastructure building  ... 
doi:10.37624/ijert/13.11.2020.3913-3918 fatcat:2w5qnskqzbabppiksfkrujjjsu

A Novel Approach for On-road Vehicle Detection and Tracking

Ilyas EL, Mohamed EL, KOUTTI, ELLAHYANI, Said CHARFI
2016 International Journal of Advanced Computer Science and Applications  
The tracking process was performed based on edge features matching approach. The Kalman filter was used to correct the measurements.  ...  vehicle, to vehicle detection and tracking.  ...  CONCLUSION In this work, a novel vehicle detection and tracking method was proposed. This method is robust in the context of real traffic scenes.  ... 
doi:10.14569/ijacsa.2016.070181 fatcat:amfddm75vffplflejqo5oxvwlu

Vision-based Vehicle Detection Survey

Alex David S, K. Antony Kumar, S. Ravi Kumar
2016 International Journal of Recent Contributions from Engineering, Science & IT  
Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion  ...  Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.  ...  In [7] , SURF: Speeded up Robust Features and edges were combined to detect vehicles in the blind spot.  ... 
doi:10.3991/ijes.v4i1.5590 fatcat:smijyealynb6ffqiybuuxftmvq

Lane Departure and Collision Controlling using Image Processing

2019 International Journal of Engineering and Advanced Technology  
Here, road lane detection, tracking method and warning alert system is proposed and implemented using MATLAB software.  ...  This paper displays the warning message for each departure of the vehicle and thus avoiding the collision.  ...  method.  ... 
doi:10.35940/ijeat.f8498.088619 fatcat:5befxqohxjasjid6ckx7xsoykm

Development of Vehicle Speed Estimation Technique using Image Processing

Nagaratna M Raikar, Ramaiah Institute of Technology,bangalure
2020 International Journal of Engineering Research and  
And then, the gradient edge detection algorithm is used for moving vehicle edge extraction. The next step is template matching by using a normalized cross-correlation method.  ...  This paper proposed a novel computer vision-based automated system for multi-vehicle detection, tracking, and estimation of vehicle speed in a video sequence by using image processing.  ...  The median is a more robust method and much better in sharp edges preserving compared to the mean filter method [16] .  ... 
doi:10.17577/ijertv9is090187 fatcat:psaonkwbmvf5vp7cswjp3j3wwe

AUTOMATIC PEDESTRIAN CROSSING DETECTION AND IMPAIRMENT ANALYSIS BASED ON MOBILE MAPPING SYSTEM

X. Liu, Y. Zhang, Q. Li
2017 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision.  ...  Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved.  ...  ACKNOWLEDGEMENTS This work was supported in part by the National Natural Science Foundation of China with project number 41571434 and 41322010.  ... 
doi:10.5194/isprs-annals-iv-2-w4-251-2017 fatcat:fji3sjq2zjcptiyt4ncgjh3pk4

Real-Time Vehicle Detection Using Cross-Correlation and 2D-DWT for Feature Extraction

Abdelmoghit Zaarane, Ibtissam Slimani, Abdellatif Hamdoun, Issam Atouf
2019 Journal of Electrical and Computer Engineering  
Vehicle detection can be exploited to accomplish several tasks such as computing the distances to other vehicles, which can help the driver by warning to slow down the vehicle to avoid collisions.  ...  In this paper, we propose an efficient real-time vehicle detection method following two steps: hypothesis generation and hypothesis verification.  ...  In our proposition, at the hypothesis generation step, vehicle candidates are determined by using cross-correlation after preprocessing using edge detection to improve the results. e cross-correlation  ... 
doi:10.1155/2019/6375176 fatcat:3v6vzvgcgjfp7aotybi46ns6aa

Robust Lane-Detection Method for Low-Speed Environments

Qingquan Li, Jian Zhou, Bijun Li, Yuan Guo, Jinsheng Xiao
2018 Sensors  
Vision-based lane-detection methods provide low-cost density information about roads for autonomous vehicles.  ...  The experimental results show that the method is robust and efficient and can meet the real-time requirements of autonomous vehicles.  ...  An improved method based on symmetrical local threshold (SLT) is proposed in this paper to provide effective and robust edge detection by adding an accuracy width constraint.  ... 
doi:10.3390/s18124274 pmid:30518167 fatcat:sp4h7pcfknhtdd3ud44eroqbvi

Multi-lane Detection Based on RMFP for Autonomous Vehicle Navigation in Urban Environments

2016 Revista de la Facultad de Ingeniería  
Lastly, the clustering method is used to generate lane lines, and these lines are tracked by frame association and Kalman Filter.  ...  This paper presents a robust and real-time multi-lane detection method based on road marking feature points (RMFP) for autonomous vehicle navigation in an urban environment.  ...  Therefore, a real-time and robust lane detection method is very important for autonomous vehicle vision navigation.  ... 
doi:10.21311/002.31.5.18 fatcat:m363mxijobcdhmxb5cxvcnl4iy

Two Images Comparison with Invariance to Illumination Properties

Jean-Philippe Tarel
2019 2019 IEEE International Conference on Image Processing (ICIP)  
Index Terms-Image comparison, invariance to illumination, bilateral filtering.  ...  Moreover, we show that the proposed operator is relatively robust to strong noise on one of the compared images.  ...  Fast implementations of the bilateral filter were proposed by several authors, see for instance [5] . These usually extends to joint/cross bilateral filters [6] .  ... 
doi:10.1109/icip.2019.8803019 dblp:conf/icip/Tarel19 fatcat:2asllubkcvci7gqharo4oclk3e

Laser-camera Compositite Sensing for Road Detection and Tracking

W.S. Wijesoma, K.R.S. Kodagoda, A.P. Balasuriya
2005 International Journal of Robotics and Automation  
However, vision alone methods for extraction of such curbs or road edge features with accurate depth information is a formidable task as the curb is not conspicuous in the vision image and also it requires  ...  Experimental results are presented to demonstrate the viability, and effectiveness, of the proposed methodology and its robustness to different road configurations and shadows.  ...  In our application, the LMS is used mainly to detect the road boundaries or edges as defined by the curbs.  ... 
doi:10.2316/journal.206.2005.3.206-2705 fatcat:w2f35tug2zbtvmbm4yxirifi2e
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