Algorithms for licenseplate detection: A survey

Farajian, Nima; Rahimi, Morteza A.

doi:10.1109/ictck.2014.7033529

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…There has been many algorithms developed for LP detection [8]. Edge detection [9], [10], Gabor filters [12], SIFT features [11] and connected component analyses [13] are some of the common techniques that are used for traditional LP detection.…”

Section: Related Workmentioning

confidence: 99%

Vehicle License Plate Detector in Compressed Domain

Beratoglu

Töreyi̇n

2021

IEEE Access

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Data compression techniques allow data size to be reduced prior to data transmission and involve decompression upon transfer. This study shows for the first time that license plate (LP) detection can be accomplished without full decompression of the encoded data. Therefore, by determining in advance which images are required for LP recognition, computational costs of the system can be reduced. The proposed approach is realized on High Efficiency Video Coding (HEVC) based compressed video sequences. Two methods are provided that generate images from HEVC attributes. Fully decoded pixel domain images are also generated for comparative purposes from the same encoded data. The YOLO V3 Tiny Object Detector is used in order to detect LPs in the generated images. EnglishLP, a public dataset, is used to interpret the findings in terms of speed and precision and for comparison with previous studies. An additional contribution of the paper is that a new compressed domain LP database has been created and made publicly available, comprising images captured by a commercial license plate recognition system. Using at least two-orders-of-magnitude less amount of data, the proposed compressed domain LP detector achieved similar precision and recall values to those of the state-of-the-art LP detection schemes tested on both datasets. Moreover, the proposed method results in more than 30% saving in inference time. The results suggest that the proposed method can be utilized for rapid video archive searching applications.

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Section: Related Workmentioning

confidence: 99%

Vehicle License Plate Detector in Compressed Domain

Beratoglu

Töreyi̇n

2021

IEEE Access

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“…The ANR (automatic number plate recognition) plays an important role in many systems like traffic monitoring system, Crime detection system, Stolen vehicle detection [1] etc. Thus, ANR is used by city traffic department to monitor the traffic as well as to track the stolen vehicle.…”

Section: Introductionmentioning

confidence: 99%

Survey on Automatic Number Plate Recognition (ANR)

Sonavane¹,

Soni²,

Majhi³

2015

IJCA

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Day by day we have been heard about the news of vehicle getting stolen from parking or from any other place in the city. So, to keep track of that stolen vehicle we should have to install the CCTV camera on every signal in the city. Also we have to install the number plate detection system which can detect the number plate of every vehicle on the traffic signal. For detecting the number plate from the moving vehicle there are many algorithm has been developed but still this area always remain evolving each every year, In number plate detection system image processing plays an important role, the system consist of basic operations preprocessing, image conversion from RGB to Gray, apply edge detection, apply morphological operators on same image then extract plate region from image and last process the plate region using OCR (optical character recognition).Every algorithm in this category always follows this basic steps, each algorithm has some pros and cons, because same algorithm cannot be useful for different environmental condition. The Algorithm's efficiency is totally depends upon the quality of input image. E.g. resolution of camera, intensity of the image, illumination of image, shadow effect etc. In this paper we are focusing on which are different algorithm has been developed so far to improve the efficiency of the number plate detection system. General TermsTemplate Matching, Neural Network.

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Learning Color Transitions to Extract Senegalese License Plates

2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Algorithms for licenseplate detection: A survey

Cited by 4 publications

References 23 publications

Vehicle License Plate Detector in Compressed Domain

Vehicle License Plate Detector in Compressed Domain

Survey on Automatic Number Plate Recognition (ANR)

Learning Color Transitions to Extract Senegalese License Plates

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