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Image-Based Licence Plate Recognition
Vacek, Michal ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
In first part thesis contains known methods of license plate detection. Preprocessing-based methods, AdaBoost-based methods and extremal region detection methods are described.Finally, there is a described and implemented own access using local detectors to creating visual vocabulary, which is used to plate recognition. All measurements are summarized on the end.
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Similar Photo Searching
Rosa, Štěpán ; Mlích, Jozef (referee) ; Beran, Vítězslav (advisor)
This paper describes the way to realization such an application, where a user chooses a photo database to working with and enters a photo into the system. The system using a visual vocabulary finds the most similar photos from the database and offers tags of the searched photo with a suitable form based on the tag statistical analysis of this photo.
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Topology Recognition from Crossroad Plan
Huták, Petr ; Bartík, Vladimír (referee) ; Kreslíková, Jitka (advisor)
This master‘s thesis describes research, design and development of system for topology recognition from crossroad plan. It explains the methods used for image processing, image segmentation, object recognition. It describes approaches in processing of maps represented by raster images and target software, in which the final product of practical part of project will be integrated. Thesis is focused mainly on comparison of different approaches in feature extraction from raster maps and determination their semantic meaning. Practical part of project is implemented in C# language with OpenCV library.
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Parametrization of Image Point Neighborhood
Zamazal, Zdeněk ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This master thesis is focused on parametrization of image point neighborhood. Some methods for point localization and point descriptors are described and summarized. Gabor filter is described in detail. The practical part of thesis is chiefly concerned with particle filter tracking system. The weight of each particle is determined by the Gabor filter.
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License Plate Detection and Recognition for Traffic Analysis
Černá, Tereza ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
This thesis describes the design and development of a system for detection and recognition of license plates. The work is divided into three basic parts: licence plates detection, finding of character positions and optical character recognition. To fullfill the goal of this work, a new dataset was taken. It contains 2814 license plates used for training classifiers and 2620 plates to evaluate the success rate of the system. Cascade Classifier was used to train detector of licence plates, which has success rate up to 97.8 %. After that, pozitions of individual characters were searched in detected pozitions of licence plates. If there was no character found, detected pozition was not the licence plate. Success rate of licence plates detection with all the characters found is up to 88.5 %. Character recognition is performed by SVM classifier. The system detects successfully with no errors up to 97.7 % of all licence plates.
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Detection of Corresponding Points in Images
Ptašek, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
Bachelor thesis is concerned with detection of corresponding points in two digital images. It summarises and describes basic, new and modern methods of detection of interest points. It also describes methods for determinating equivalence of image parts. Work itself includes design of application and describes implementation of corresponding points detector based on segmentation method MSER. Application was written in C programming language and uses Open CV graphic library under Windows XP operating system. Results that summarise characteristics of detector illustrate potential of chosen methods.
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Region Detectors and Descriptors in Image
Žilka, Filip ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master’s thesis deals with an important part of computer vision field. Main focus of this thesis is on feature detectors and descriptors in an image. Throughout the thesis the simplest feature detectors like Moravec detector will be presented, building up to more complex detectors like MSER or FAST. The purpose of feature descriptors is in a mathematical description of these points. We begin with the oldest ones like SIFT and move on to newest and best performing descriptors like FREAK or ORB. The major objective of the thesis is comparison of presented methods on licence plate localization task.
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Methods for precise local affine frame constructions on MSERs
Mikulík, Andrej
Feature detection and matching is a fundamental problem in many applications in computer vision. We propose a novel approach that improves repeatability and precision of Local Affine Frames (LAFs) constructed on discretized contours detected by Maximally Stable Extremal Regions (MSERs) detector. Proposed method reconstructs a discretized contour of extremal region by taking into account the intensity function in local neighborhood of the contour points. Additionally we propose a new method for detection of local curvature extrema, based on the refined contour. The extensive experimental evaluation on publicly available datasets showed higher number of correspondences and higher inlier ratio in more than 80\% of the image pairs. Since the procesing time of the contour refinement is negligible, there is no reason not to include the proposed algorithms as a standard extension of MSER detector. Powered by TCPDF (www.tcpdf.org)
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Similar Photo Searching
Rosa, Štěpán ; Mlích, Jozef (referee) ; Beran, Vítězslav (advisor)
This paper describes the way to realization such an application, where a user chooses a photo database to working with and enters a photo into the system. The system using a visual vocabulary finds the most similar photos from the database and offers tags of the searched photo with a suitable form based on the tag statistical analysis of this photo.
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Methods for precise local affine frame constructions on MSERs
Mikulík, Andrej
Feature detection and matching is a fundamental problem in many applications in computer vision. We propose a novel approach that improves repeatability and precision of Local Affine Frames (LAFs) constructed on discretized contours detected by Maximally Stable Extremal Regions (MSERs) detector. Proposed method reconstructs a discretized contour of extremal region by taking into account the intensity function in local neighborhood of the contour points. Additionally we propose a new method for detection of local curvature extrema, based on the refined contour. The extensive experimental evaluation on publicly available datasets showed higher number of correspondences and higher inlier ratio in more than 80\% of the image pairs. Since the procesing time of the contour refinement is negligible, there is no reason not to include the proposed algorithms as a standard extension of MSER detector. Powered by TCPDF (www.tcpdf.org)
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