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Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.
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Automatic Face Recognition in Real Environment
Kičina, Pavol ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This master‘s thesis describes the identification faces in real terms. It includes an overview of current methods of detection faces by the classifiers. It also includes various methods for detecting faces. The second part is a description of two programs designed to identify persons. The first program operates in real time under laboratory conditions, where using web camera acquires images of user's face. This program is designed to speed recognition of persons. The second program has been working on static images, in real terms. The main essence of this method is successful recognition of persons, therefore the emphasis on computational complexity. The programs I used a staged method of PCA, LDA and kernel PCA (KPCA). The first program only works with the PCA method, which has good results with respect to the success and speed of recognition. In the second program to compare methods, which passed the best method for KPCA.
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Cryptanalysis using neural networks
Budík, Lukáš ; Mačák, Jaromír (referee) ; Martinásek, Zdeněk (advisor)
This dissertation deals with analysis of current side canal by means of neural network. First part describes basis of cryptografy and dilemma of side canal. In the second part is theoretickly described neural network and correlative analysis. Third part describes practical analysis of calibres of current side canals by means of classifier which uses neural network in Matlab surrounding. This classifier is confronted with classifier which uses correlative analysis.
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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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Establishing speaker's age and sex
Rendek, Tomáš ; Pfeifer, Václav (referee) ; Atassi, Hicham (advisor)
This work deals with speaker´s age and gender recognition. At the beginning it introduces the practical usage of this application and discusses the solutions available. The theoretical part of the thesis specifies the feature extraction and reduction methods and speech databases used in the experiments. The practical part describes the recognizer implemented in the Emotional tool and in two chapters describes the individual experiments. Regarding speaker´s gender estimation; we focused on the impact of the emotional state and speaker's age on the classification process. The two remain experiments were dedicated for general gender estimation performed by using two different classifiers – GMM and k-NN. These two classifiers were used in age estimation as well. In this case, four Group of age was formed and two different feature sets namely: segmental and suprasegmental were exploited four groups
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Neural networks for EMC modeling of small airplanes
Koudelka, Vlastimil ; Goňa,, Stanislav (referee) ; Raida, Zbyněk (advisor)
This thesis deals with neural modeling of electromagnetic field inside small aircrafts, witch can contain composite materials in their construction. Introduction to neural networks and its application in EMC of small airplanes is discussed in the first part of the text. In the second part of this thesis we design a simple EM model of small airplane. The airplane is simulated by two parallel dielectric layers (the left-hand side wall and the right hand side wall of the airplane). The layers are put into a rectangular metallic waveguide terminated by the absorber in order to simulate the illumination of the airplane by the external wave (both of the harmonic nature and pulse one). Numerical analyses are performed to search the relations between the distribution of an electromagnetic field inside the aircraft and electric parameters of model walls. The results of numerical analyses are used to train two types of neural network. In this way we can obtain accurate continuous model of electromagnetic field inside the aircraft. For the comparison with neural networks a multi-dimensional cubic spline interpolation is provided also. Neural classifiers are also investigated. We use them for classification of imaginary composite materials in terms of EMC. The nearest neighbour algorithm is applied as a classic approach to problem of classification.
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Comparison of architectures of MIB system databases designed for QoS management in data networks
Jelínek, Tomáš ; Hošek, Jiří (referee) ; Molnár, Karol (advisor)
Bachelor thesis deals with Diffserv mechanism for Quality of Service in data network and goes through several parts of structure MIB database for managing Diffserv mechanism. The first chapter is introduction. I explain SNMP protocol in the second chapter. In the third chapter I deal with Quality of Service (QoS) and in the next chapter I explain Diffserv mechanism and its architecture. In fifth chapter I present possibilities of using Policy Information Base (PIB). I show several parts of MIB database in the sixth chapter. I compare two parts of MIB database and summary whole work in the last chapter.
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Face recognition
Škrobák, Dalibor ; Číka, Petr (referee) ; Kyselý, František (advisor)
This thesis is focused on face detection in static picture. Theoretical part contains color spaces (RGB, HSI, YCbCr), methods for skin detection (explicit, parametric or non-parametric methods), image metric, edge detection, mathematical morphology, methods for classification faces (appearance-based methods, feature invariant approaches, knowledge-based methods, template matching methods). Practical part of this thesis contains concept and practical realization two algorithms for segmentation skin in static image (simple method based on Cr chroma components and statistical method). Practical part contains concept and practical realization two algorithms for classification face (appearance-based method and template matching method) too.
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Influence of Metric on Classification Error of Distance-Based Classifiers
Jiřina, Marcel
Five types of classifiers that use sample distances for class estimation of an unknown sample was tested. Each classifier was tested with fifteen different metrics on 24 classification tasks from the UCI Machine Learning Repository. The metrics were compared and the best of them was found for each classifier. Surprisingly, the best metrics for all five types of classifiers is the Hassanat metrics. Classifiers were also compared and ranked according to their classification ability. Wilcoxon Test and Friedman Aligned test were used for statistical evaluation.
Fulltext: content.csg -  PDF
Plný tet: v1211-14 - PDF
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