Feature-based tracking approach for detection of moving vehicle in traffic videos

Dallalzadeh, Elham; Guru, D. S.

doi:10.1145/1963564.1963609

Cited by 9 publications

(6 citation statements)

References 17 publications

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“…In practical applications, the rate of license plate recognition is closely related to the quality of images and videos (Dallalzadeh & Guru, 2010). The license quality will be affected by various reasons, such as rusting, paint peeling, font fade, license plate obscured, license plate tilt, bright reflective, multiple licenses, fake license and so on.…”

Section: ) License Plate Character Segmentationmentioning

confidence: 99%

Rotation correction for license plate recognition

Nguyen

Yan

2018

2018 4th International Conference on Control, Automation and Robotics (ICCAR)

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The focus of this thesis is on reliable and robust license plate recognition (LPR). The technology is currently in operation that both the quantity and quality-based approaches are needed. The entire procedure of license plate recognition consists of six steps: (1) image acquisition, (2) image pre-processing, (3) plate locating, (4) character segmentation, (5) character recognition, (6) output. However, when a road is uneven and slant, a vehicle will be shaky while running; consequently, the plate is also unstable and tilted with an angle of rotation at this moment. Meanwhile, a surveillance camera is very difficult to capture an effective image so that the plate is hard to be located and recognized. Due to this existing problem, the contributions of this thesis are: (1) plate tilt correction using Hough transform; (2) GNN-based plate number recognition. The novelties of this thesis are to improve the robustness and reliability of license plate recognition through literature review as well as evaluate those existing technologies.

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Section: ) License Plate Character Segmentationmentioning

confidence: 99%

Rotation correction for license plate recognition

Nguyen

Yan

2018

2018 4th International Conference on Control, Automation and Robotics (ICCAR)

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“…Because of the challenges involved in tracking objects as discussed in previous section, a lot of work have been carried out on object tracking and these approaches can be classified as region based [7][8][9] , feature based [10][11][12][13] , model based [14][15][16][17][18][19][20] and hybrid [21][22][23][24][25]. The region based methods track object by observing the regions of motion object.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In order to represent the object blob by good features which will help in robust tracking, Hu moments of object blob are also extracted. Based on the normalized central moments the seven Hu moments invariant for object blob is computed using the equations (4) through (10). After the motion segmentation stage, there may by some noise whose area will be considerably small is size.…”

Section: Motion Segmentation Using Chi Square Statisticsmentioning

confidence: 99%

Multiple Objects Tracking in Surveillance Video Using Color and Hu Moments

Chandrajit¹,

Girisha²,

Vasudev³

2016

SIPIJ

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“…In this suggestion, the calculationamongpresent image and backdrop image has carry out depend on doorsill level and they use a morphological filter to remove the noise associated with the process. The movement detection has been displayed by overcome the drawback of background subtraction algorithm in [20]. They compute the background subtraction algorithm and utilize the capability to determine the matter of restrictedlighting change.…”

Section: Introductionmentioning

confidence: 99%

Pathway Discover of Moving Objects using Color Segmentation and Region property

Abood¹,

Faisal²,

Hussein³

2019

IJET

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This paper presents the real time algorithm of moving objects tracking and detection using region property and color segmentation. The real time of moving objects pathway finder is a vitaldifficultyproblem in human computersinterface and video observation. The attitude of track and detect a moving objects using color characteristic and movements has introduced with new techniques for automation. The tracking of video is a method of discovery the travelthing over specific reserve by use a color camera to narrate target bodies in successive video borders. Respecting to frame rate, the relationship could be especially troublesome in case of speedy moving of objects.In interchange case, the issue grows of randomness is the time in case of the tracking objects varying the direction following eventually. For this cases, the video tracking design model are classicallyexploit the progress model willportrays process the image of the target when it CHANGE for characteristicimaginableobjects movements. A development of tracking algorithm to the real time affecting bodies with unlike frames of the videotape by use color characteristic and movement is investigated and produced in this work.

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Feature-based tracking approach for detection of moving vehicle in traffic videos

Cited by 9 publications

References 17 publications

Rotation correction for license plate recognition

Rotation correction for license plate recognition

Multiple Objects Tracking in Surveillance Video Using Color and Hu Moments

Pathway Discover of Moving Objects using Color Segmentation and Region property

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