Document Type
Honors Thesis
Abstract
The License Plate Recognition Advanced Parking System is a fully automated parking enforcement system that is able to identify license plate information of cars as they pull into a parking lot and track these cars to their individual parking spots after they have entered. This allows an administrator to view exactly where each car is parked and enforce parking rules down to a per spot level accuracy. Computer vision techniques are used to read license plates as cars enter the parking lot and additional cameras will track each car to its individual spot. The disabled parking pass component of this project is the feature to detect disabled parking passes on cars as they enter and validate the cars that can park in disabled parking spots using this information. This will be implemented using a convolutional neural network and computer vision techniques to detect and identify these passes in a video input.
Publication Date
5-1-2020
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Perappadan, Thomas, "DISABLED PARKING PASS DETECTOR FOR LICENSE PLATE RECOGNITION PARKING SYSTEM USING A CONVOLUTION NEURAL NETWORK AND TRANSFER LEARNING" (2020). 2020 Spring Honors Capstone Projects. 44.
https://mavmatrix.uta.edu/honors_spring2020/44