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Automatic Number Plate Recognition for Android
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis describes how we utilize machine learning and image preprocessing to create a system that can extract a license plate number by taking a picture of a car with an Android smartphone. This project was provided by ÅF at the behalf of one of their customers who wanted to make the workflow of their employees more efficient.

The two main techniques of this project are object detection to detect license plates and optical character recognition to then read them. In between are several different image preprocessing techniques to make the images as readable as possible. These techniques mainly includes skewing and color distorting the image. The object detection consists of a convolutional neural network using the You Only Look Once technique, trained by us using Darkflow.

When using our final product to read license plates of expected quality in our evaluation phase, we found that 94.8% of them were read correctly. Without our image preprocessing, this was reduced to only 7.95%.

Place, publisher, year, edition, pages
2019. , p. 56
Keywords [en]
machine learning, neural network, computer vision, ocr, object detection
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kau:diva-72573OAI: oai:DiVA.org:kau-72573DiVA, id: diva2:1325108
External cooperation
ÅF
Subject / course
Computer Science
Educational program
Study Programme in IT design, 180 hp
Supervisors
Examiners
Available from: 2019-06-26 Created: 2019-06-14 Last updated: 2019-06-26Bibliographically approved

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Computer Sciences

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf