|
|
LPR Recognition
Trkal, Ondřej ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
The thesis deals with analysis and design of system for automatic localization and recognition of the license plate. The input images are from different sources, and contain large scenic and weather variations. The aim was to create a system able to find the licence plate on the image and recognize its alphanumeric figure. In this work, there is a focus on analysis and implementation of localization and optical character recognition methods. One own and four other localization methods are compared. There are also compared three classifiers for optical character recognition. Localization and OCR methods are tested on real data and evaluated in accordance with the calculated evaluation parameters. The work also contains sensitivity analysis of the proposed system.
|
|
|
Number Plate Recognition using Deep Learning Techniques
Dobrovský, Ladislav ; Dvořák, Jiří (referee) ; Matoušek, Radomil (advisor)
Focus of this thesis is research of deep convolutional artificial neural networks and their usage as solution to automatic license plate recognition problem. After summary of theory and current trends the further direction of development has been chosen. Thesis investigates several types of convolutional neural networks and complex architecture of system of collaborating applications. In practical part is described implementation and results of experiments with assessment of networks’ suitability for practical use.
|
|
|
Number Plate Recognition using Deep Learning Techniques
Dobrovský, Ladislav ; Dvořák, Jiří (referee) ; Matoušek, Radomil (advisor)
Focus of this thesis is research of deep convolutional artificial neural networks and their usage as solution to automatic license plate recognition problem. After summary of theory and current trends the further direction of development has been chosen. Thesis investigates several types of convolutional neural networks and complex architecture of system of collaborating applications. In practical part is described implementation and results of experiments with assessment of networks’ suitability for practical use.
|
|
|
LPR Recognition
Trkal, Ondřej ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
The thesis deals with analysis and design of system for automatic localization and recognition of the license plate. The input images are from different sources, and contain large scenic and weather variations. The aim was to create a system able to find the licence plate on the image and recognize its alphanumeric figure. In this work, there is a focus on analysis and implementation of localization and optical character recognition methods. One own and four other localization methods are compared. There are also compared three classifiers for optical character recognition. Localization and OCR methods are tested on real data and evaluated in accordance with the calculated evaluation parameters. The work also contains sensitivity analysis of the proposed system.
|
guest ::
