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%.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kau-72573 |
| Date | January 2019 |
| Creators | Larsson, Stefan, Mellqvist, Filip |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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