Automatic Vehicle Number Plate Recognition System Using Machine Learning

Kumar, Jai; Sujatha, B.; Leelavathi, N.

doi:10.1088/1757-899x/1074/1/012012

Cited by 23 publications

(3 citation statements)

References 5 publications

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“…J M S V Ravi Kumar et.al. [10], presented One type of (STDM) smart transportation / detection number plate recognition (NPR) model by using digitally acquired photos, the specific application strongly enables the model for recognizing and automatically reading the license plate of a specific car. This effort extracts the vehicle's number plate from the image using mathematical morphological techniques (erosion, stretching).…”

Section: Fig 3 Database Of Templatesmentioning

confidence: 99%

Comparison Study About Vehicle Detection and Plate Number Recognition

Imran Alhussein,

Mohammedbaqer Qazzaz

2023

JQCM

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Vehicle detection is crucial to the management of Intelligent Transportation Systems of urban traffic. Optical character recognition is many systems use, like the automatic number plate recognition system (NPR). Using various techniques and methodologies, such as convolution or deep neural networks, morphological operations, optical character recognition, and edge detection, such a system has been widely utilized to identify car license plates. Numerous applications algorithms of vehicle identification become possible after the development of many helpful techniques in computer vision and the availability number of related images as a dataset. In this paper, the various plate numbers of the specific vehicle will be and reviewed. Vehicle detection systems suffer from a variety of difficulties and constraints such as the all the surrounding state of clarity for the license plate, non-standard formats of the plate, complex situations, camera quality and clarity, the position and distance of the camera, the distortion in the image, contrast issues, reflections and the state day and night images As a result, numerous methods for comprehending and assessing the idea behind the vehicle number plate recognition systems have been presented with simply explaining the importance and drawbacks of each system.

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Section: Fig 3 Database Of Templatesmentioning

confidence: 99%

Comparison Study About Vehicle Detection and Plate Number Recognition

Imran Alhussein,

Mohammedbaqer Qazzaz

2023

JQCM

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“…The object to be detected is gathered from certain sources such as video, picture, or any image resources. Some implementations of object detection are Vehicle Number Plate [1,2], people head count [3], face recognition [4], face mask recognition [5], real time human detection [6], and many other application.…”

Section: Introductionmentioning

confidence: 99%

Speed and Accuracy Comparison of Person Detection Using Pretrained CenterNet and Yolov3

Friendly,

Harizahayu,

Sembiring

2024

IJRVOCAS

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Implementations of object detection by using common devices for general purpose application is not widely used for speed and prone to errors. Most of research in speed detection using known method such as Centernet, Yolov3, Fast-RNN has variant result since the computer used are different. This experiment try to conduct experiments for person detection with Centernet and Yolov3 method using commonly used computer only using CPU. Based on the experiments, Yolov3 can give a much better precision for person detection by 98.42% of mAP point while Centernet only 97%. In terms of processing speed, Centernet can give much better speed where it can detect a person in average 370ms better than Yolov3 with average of 1050 ms or 1 second.

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“…Following the completion of the aforementioned procedures, the segmentation method is now being used to locate the text on the license plate using OCR and template matching. This technique can rapidly and reliably identify the license plate number from an image of the car [9]. India has a population of about 1.3 billion people, and every individual there owns at least one vehicle.…”

Section: Introductionmentioning

confidence: 99%

Advantages of Automated License Plate Recognition Technology

Ahmad,

Musa,

Dahiru

et al. 2024

Middle East Res J Engr Technol

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Automatic Number Plate Recognition (ANPR) is a technology that can be utilized by mall and movie theater parking management as well as toll booths on roads, expressways, etc. to expedite the toll collection process. Automated systems to retain vehicle information are becoming more and more important as the number of vehicles rises. It is imperative that communication be prioritized in order to effectively manage traffic and reduce crime. Number plate recognition is a dependable technique for automatic vehicle identification. With current algorithms, which are based on the concept of learning, developing adequate outcomes takes a long time and a lot of experience. An innovative use of machine learning is Automatic Number Plate Detection, which recognizes photos and transforms them into text. Using picture segmentation, the system locates, picks up, and extracts the vehicle's image and number plate. Afterwards, optical character recognition technology is used to identify characters in the retrieved image. This technology is used in military zones, apartment buildings, and traffic surveillance.

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Automatic Vehicle Number Plate Recognition System Using Machine Learning

Cited by 23 publications

References 5 publications

Comparison Study About Vehicle Detection and Plate Number Recognition

Comparison Study About Vehicle Detection and Plate Number Recognition

Speed and Accuracy Comparison of Person Detection Using Pretrained CenterNet and Yolov3

Advantages of Automated License Plate Recognition Technology

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