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Bifurcation Localization in Retina Images
Pres, Martin ; Drahanský, Martin (referee) ; Semerád, Lukáš (advisor)
From biometrical point of view, main features of retina are fovea, optic nerve and blood vessel tree. Blood vessel tree is unique for each person and this biological feature is used in biometric systems for person-recognition by retinal images. This document describes methods for optic disc and fovea localization, method for vessel tree segmentation, which is based on well-known \emph{Matched filters} method and also describes method for localization of blood vessel bifurcations. Main goal of this thesis is creation of program which can automatically preprocess input image, segment blood vessels and localize vessel bifircations. The program is implemented in Java with OpenCV library.
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Information System Supporting Feature-Driven Development
Tichá, Pavlína ; Zendulka, Jaroslav (referee) ; Rychlý, Marek (advisor)
This thesis deals with the Featured Driven Development (FDD) agile methodics. To support this methodics, an information system has been created, providing all team-members with instruments to follow the methodics. This multi-user system is implemented as a web-based application, enabling creation of a feature list, plan a project, support the cooperation among the feature team members and watch the project progress in an illustrative way. To improve the visualization possibilities, a wide range of reports aimed at the company management and the client is provided.
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Face Detection in Camera Image on a Mobile Phone
Tureček, Martin ; Láník, Aleš (referee) ; Herout, Adam (advisor)
This thesis deals with a face detection on mobile phones. It especially focuses on Windows Mobile platform. The introduction is therefore devoted to this operating system and alternatives of working with the camera. The next part of the text refers to general problems of the face detection in the image considering the weak performance of the target device. Another part of this thesis is a description of the acquisition of images from the camera using DirectShow multimedia framework and creation of a custom transformation filter for the face detection. Achieved results are summarized in the conclusion. It takes a form of tests examining different mobile devices. All difficulties arising during Windows Mobile developing are also mentioned.
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Automatic vocal-oriented recognition of human emotions
Adamský, Aleš ; Kubánková, Anna (referee) ; Atassi, Hicham (advisor)
This work deals with the characteristics, formation, representation and analysis of speech and the speech signal. It explains the details of concepts such as emotions and prosody. It analyzes different emotion state of human, as well as prosodic parameters: intensity, harmonisity and formants. It includes a database emotional states of human. This database was analyzed using the Praat and suitable features were selected for detecting of emotional states of human speech. It also deals with neural networks. It contains a description of Java Neural Network Simulator, which is used to detect emotional states of human speech. Results of recognition are processed in tables and graphs for easier navigation.
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Multilingual analysis of human emotional states
Rendek, Tomáš ; Koula, Ivan (referee) ; Atassi, Hicham (advisor)
This work deals with the properties of the speech signal. At the beginning it introduces a process of generation of the speech. Then, it covers the prosodic features of the speech, which represent a related characteristic of emotions. It defines an emotion itself, as well as the basic features and parameters of the human speech. For the analysis we use the program called Praat. As it is an unknown program, we devote a part of the work to it, which acquaints us with its advantages. The next part of this paper comprises also two enclosed databases containing records of particular emotional states of human. These databases were created and collected for Slovak and German language. However, none of them contain spontaneous material. Next, the work concerns a concept of the neural networks. It regards it as a possible realization of recognizing of emotional characteristics. The initial analysis presents large number of gained features, out of which only the best twelve were selected on the basis of geometric separability. These features are distinct for both sexes, as well as for both nationalities. Consequently, they are used for training with a neural network. The work concludes by summarizing of the results discussing the successfulness with recognition of emotional states. It also gives possible reasons which lead to degradation of their successful classifying. The thesis contains a CD with all the partial and ultimate results, and files with records for Slovak and German language.
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Image similarity measurement using points of interest
Jelínek, Ondřej ; Uher, Václav (referee) ; Burget, Radim (advisor)
This paper presents a new object detection method. The method is based on keypoints analysis and their parameters. Computed parameters are used for building a decision model using machine learning methods. The model is able to detect object in the picture based on input data and compares its similarity to the chosen example. The new method is described in detail, its accuracy is evaluated and this accuracy is compared to other existing detectors. The new method’s detection ability is by more than 40% better than detection ability of detectors like SURF. In order to understand the object detection this paper describes the process step by step including popular algorithms designed for specific roles in each step.
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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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Automatic vocal-oriented recognition of human emotions
Houdek, Miroslav ; Přinosil, Jiří (referee) ; Atassi, Hicham (advisor)
This master thesis concerns with emotional states and gender recognition on the basis of speech signal analysis. We used various prosodic and cepstral features for the description of the speech signal. In the text we describe non-invasive methods for glottal pulses estimation. The described features of speech were implemented in MATLAB. For their classification we used the GMM classifier, which uses the Gaussian probability distribution for modeling a feature space. Furthermore, we constructed a system for recognition of emotional states of the speaker and a system for gender recognition from speech. We tested the success of created systems with several features on speech signal segments of various lengths and compared the results. In the last part we tested the influence of speaker and gender on the success of emotional states recognition.
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Automatic / Automated recogniton of emotional states based on utterance analysis
Pfeifer, Leon ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis deals with the analysis of human emotional states. The thesis consists of three parts. The first part is charcterize, the process of speech generating, from phonetic and psychological poin of view. In the second part there are proccesed metods and contextual things.(preprocessing of signal, voice activity detector). For calculation fundamental Frequency it was used metod of central clipping, another used metod is formant frequency analyse and the last is metod of determinatin of nuber of thorns and planes. In the thirt part there are proccesesed results of measurements performed by particural metods. It was scorred five different emotional states: neutral, anger, happiness, sadness and surprise. At the end of this part there are discussed results for each metod.
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Identification of emotional state using speech signal analysis
Navrátil, Michal ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis deals with the analysis of human emotional states speaker by the help of analyse speech signals. The thesis has two parts. In the first part, the process of speech generating is described in addition to the description of the commonly used pre-processing methods such as denoising or preemphasis. The first part also deals with the major and minor prosody features, these features are: the fundamental frequency, energy, spectral features and time domain features such as the speech rate. The second part of this thesis deals with a task of emotion recognition from the speech signal. When we accumulate sufficient of the number of recordings emotive state will be able to rekognize emotive state with high probability. All project is prepared for use in real time. The last part of this thesis thesis contains description and results of the experiments made on a large number of speech records.
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