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Bengali Font Based Number Plates Recognition System

Bengali Font Based Number Plates Recognition Systemvon Tanvir Ahmed Siddique Sie sparen 14% des UVP sparen 14%
Über Bengali Font Based Number Plates Recognition System

This book is on Bengali language based on vehicle number plate recognition. The need for an efficient parking system stems from increased congestion, motor vehicle pollution. The aim of this research is to develop and implement an automatic system that will increase convenience and security of the parking lot with minimum human involvement. This is done with the combination of automated license plate recognition and database manipulation. The image is acquired from a live video feed by comparing frames for significant changes. Then it is passed through several steps including some diverse types of algorithms and methodologies such as Canny Edge Detection, Connected Component Labeling and Hough Transformation to localize the license plate. Subsequently, the license plate is progressed through Character Segmentation and Pattern Recognition to extract the data for manipulating and computing using database to manage the parking lot system efficiently. The system was experimented on 20 different license plates and the algorithms worked correctly in all cases with a very good response time.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9786202487429
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 52
  • Veröffentlicht:
  • 1. Februar 2018
  • Abmessungen:
  • 150x4x220 mm.
  • Gewicht:
  • 96 g.
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  Versandfertig in 1-2 Wochen.
Verlängerte Rückgabefrist bis 31. Januar 2025

Beschreibung von Bengali Font Based Number Plates Recognition System

This book is on Bengali language based on vehicle number plate recognition. The need for an efficient parking system stems from increased congestion, motor vehicle pollution. The aim of this research is to develop and implement an automatic system that will increase convenience and security of the parking lot with minimum human involvement. This is done with the combination of automated license plate recognition and database manipulation. The image is acquired from a live video feed by comparing frames for significant changes. Then it is passed through several steps including some diverse types of algorithms and methodologies such as Canny Edge Detection, Connected Component Labeling and Hough Transformation to localize the license plate. Subsequently, the license plate is progressed through Character Segmentation and Pattern Recognition to extract the data for manipulating and computing using database to manage the parking lot system efficiently. The system was experimented on 20 different license plates and the algorithms worked correctly in all cases with a very good response time.

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