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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM20852

Helmet Detection and Number Plate Recognition using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM20852

Volume:

7 |

5 |

May 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

BJ

Bela Jagtap

SS

Sujit Sawant

SS

Snehal Soundane

PG

Prashant Gaikwad

DS

Dipti Survase

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Abstract

Motorcycles have always been the primary mode of transportation in developing countries. Motorcycle accidents have increased in recent years. One of the main reasons for fatalities in accidents is that a motorcyclist does not wear a protective helmet. The most common way to ensure that motorcyclists wear a helmet is by traffic police to manually monitor motorcyclists at road junctions or through CCTV footage and to penalize those without a helmet. But it requires human intervention and effort. So this system proposes an automated system for detecting motorcyclists who do not wear a helmet and retrieving their motorcycle number plates from CCTV video footage. First, the system classifies moving objects as motorcycling or non-motorcycling. In the case of a classified motorcyclist, the head portion is located and classified as a helmet or non-helmet. Finally, for the motorcyclist identified without a helmet, the number plate of the motorcycle is detected and the characters on it are extracted by using the OCR algorithm.

KEYWORDS

CCTV IARC OCR (Optical Character Recognition) IARC (International Agency of Research on Cancer) CNN (Conventional Neutral Network) CT (Commutate Tomography) YOLO

Cite This Article

Bela Jagtap, Sujit Sawant, Snehal Soundane, Prashant Gaikwad, Dipti Survase, "Helmet Detection and Number Plate Recognition using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 5, May 2023.

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Publication Date

5/13/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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