National Repository of Grey Literature 17 records found  previous11 - 17  jump to record: Search took 0.01 seconds. 
Automatic Segmentation of Documents Stored as Images
Jakub, Dušan ; Španěl, Michal (referee) ; Szőke, Igor (advisor)
This work deals with dividing the documents stored as images into three groups of segments - background, text and graphics. It introduces various solutions and the method using Gabor filters and artficial neural networks is described in detail. The selection of apropriate settings of the filters and training parameters of the network is discussed. Connected components searching is used for improving the results. A classifier writen in C++ and OpenCV library is part of the work. The designed procedure is applied for segmentation of scanned scientific papers, but also the results of segmentation of more complex documents (advertisements, presentation slides) are presented.
Detection of Fingerprint Area in Image
Doležel, Michal ; Drahanský, Martin (referee) ; Lodrová, Dana (advisor)
This master's thesis deals with proposal and implementation of system for detection of fingerprint area in image. The first task was to elaborate the theory which is necessary for understanding the image fingerprint area detection problems. It is also necessary to propose a specific system for image fingerprint area detection where it is possible to enhance or improve present methods or design a new one. The proposed system making use of selected method will be able to avoid all problems arising during fingerprint area detection. Description of proposed system implementation and testing on the fingerprint database is described in following part. In last part all the achieved results are discussed.
Neural Network Based Image Segmentation
Vrábelová, Pavla ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
This paper deals with application of neural networks in image segmentation. First part is an introduction to image processing and neural networks, second part describes an implementation of segmentation system and presents results of experiments. The segmentation system enables to use different types of classifiers, various image features extraction and also to evaluate the success of segmentation. Two classifiers were created - a neural network (self-organizing map) and an algorithm K-means. Colour (RGB and HSV) and texture features and their combinations were used for classification. Texture features were extracted using a set of Gabor filters. Experiments with designed classifiers and feature extractors were carried out and results were compared.
Video-Based Human-Computer Interface
Caha, Miloš ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
A bachelor thesis deals with methods about a detection of direction of look and with theirs following applications for PCs control. The thesis summarises and describes the most widely used methods for individual phases of the mentioned detection. Especially, use of a face detector and of convolution filters for searching of significant points in the face is used. The work is concentrated on a design and a description of an implementation of the application which demonstrates the method of contactless PCs control.
Image search using similarity measures
Harvánek, Martin ; Mašek, Jan (referee) ; Burget, Radim (advisor)
There are these methods implemented: circular sectors, color moments, color coherence vector and Gabor filters, they are based on low-level image features. These methods were evaluated after their optimal parameters were found. The finding of optimal parameters of methods is done by measuring of classification accuracy of learning operators and usage of operator cross validation on images in program RapidMiner. Implemented methods are evaluated on these image categories - ancient, beach, bus, dinousaur, elephant, flower, food, horse, mountain and natives, based on total average precision. The classification accuracy result is increased by 8 % by implemented modification (HSB color space + statistical function median) of original method circular sectors. The combination of methods color moments, circular sectors and Gabor filters with weighted ratio gives the best total average precision at 70,48 % and is the best method among all implemented methods.
Analysis of Retinal Images Aimed to Nerve Fiber Layer Detection
Spáčil, Michal ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Goal of this work is to theoretically develop and then program a system in Matlab environment to be used as a detection tool for layer of retinal neuron pathways . First part engages oneself upon the problem of analysis within spectral plane and results of using filters conceived upon statistical occurrences of certain frequencies in used samples. Second part than deals with use of gabor filters to detect neuron pathways and the statistical results gained by their use. Based on the results an analysis tool was programmed.
Real-time Facial Feature Tracking
Peloušek, Jan ; Mekyska, Jiří (referee) ; Přinosil, Jiří (advisor)
This thesis considers the problematic of the object recognition in a digital picture, particularly about the human face recognition and its components. There are described the basics of the computer vision, the object detector Viola-Jones, its computer realization with help of the OpenCV libraries and the test results. This thesis also describes the accurate system of the facial features detection per the algorithm of the Active Shape Models and also related mechanism of the classifier training, including the software implementation.

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