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Methods for biomedical image signal segmentation
Krumpholc, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work deals with methods of segmentation of biomedical image signals. It describes, sums up and compares representative methods of digital image processing. Segmentation based on parametric representation is one of the mentioned methods. So as the basic parameter can be chosen for example luminance and the final binary image is obtained by thresholding. Next described method is segmentation based on edge representation. This method can be divided into edge detection by the help of edge detectors and of Hough transformation. Edge detectors work with the first and second derivation. The following method is region-based segmentation, which can be used for a image with noise. This category can be divided into three parts. The first one is segmentation via splitting and merging regions, when the image is split and the created regions are tested on a defined condition. If the condition is satisfied, the region merges and doesn’t continue splitting. The second one is region growing segmentation, when adjacent pixels with a similar intensity of luminance are grouped together and create a segmentated region. Third one is watershed segmentation algorithm based on the idea of water diffusion on uneven surface. The last group of methods is segmentation via flexible and active contours. Here is described an active shape model proceeding from a possibility to deform models so that they match with sample shapes. Next I also describe method Snakes, where occurs gradual contour shaping up to the edge of the object in the image. For the final editing is used mathematical morphology of segmentated images. I aimed to meet methods of image signals segmentation, to cover the chosen methods as a script in programming language Matlab and to check their properties on images.
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Object tracking in video
Boszorád, Matej ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with the issue of tracking multiple objects in a video, specifically focusing on non-learning algorithms. The first chapter represents the theoretical part of the thesis, in which some of the often used tracking methods are described, such as mean-shift, scale-invariant object transformation, Kalman filter, particle filter and Gabor wavelet transformation. These algorithms are broken down by properties they use for proper tracking. The chapter also contains section assignment problem, which is mainly concerned with Hungarian algorithm. The next part describes options of merging multiple tracking methods that are broken down by construction type into parallel, cascade, weighted and discriminatory with example for each one. Moreover there is described adaptability of the tracking system. Bellow are described problems which may occur during tracking and possible solutions to them. This section consists of a solution of image noise, changes in illumination, appearance and extinction of an object, focusing mainly on solving the problem of object occlusion. Within the practical part is created algorithm composed of different types of tracking, the results of which are then compared with selected tracking systems from the multiple object tracking benchmark. The practical part includes the tools used and the explanation of the design, in which the main classes and methods used for the tracking are explained. Besides that, this section describes parallel merging and tracking adaptability . The results of the thesis contain a comparison of the use of tracking techniques separately and together. To compare the results, videos for pedestrian tracking and face tracking were used. This thesis was based on the assumption that merging multiple monitoring systems will help with the improvement of the tracking, which was confirmed by the results.
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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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Using the Kinect sensor in detection of people
Janás, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
Bachelor thesis deals with the methods of people detection by using Microsoft Kinect. Depth image captured by this device is further processed by using standard algorithms from freely available OpenCV library. All of image processing methods are described in detail of their function and influence to image. The practical part of the work is focused on the realization of a simple program, which is serving for image segmentation and finding people.
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Height Measurement in Digital Image
Olejár, Adam ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The aim of this paper is a summary of the theory necessary for a modification, detection of person and the height calculation of the detected person in the image. These information were then used for implementation of the algoritm. The first half reveals teoretical problems and solutions. Shows the basic methods of image preprocessing and discusses the basic concepts of plane and projective geometry and transformations. Then describes the distortion, that brings into the picture imperfections of optical systems of cameras and the possibilities of removing them. Explains HOG algorithm and the actual method of calculating height of person detected in the image. The second half describes algoritm structure and statistical evaluation.
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Face recognitions in images
Krhut, Miloš ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The master thesis deals with the topic of detecting faces in digital images. There are generally described and classified the most frequently used methods and discussed their advantages and disadvantages. More detailed is described skin color detection, eye and mouth detection and are teoretically described machine learning algorithms and detection based on Haar-classifiers. The work aims to implementation of these methods in the OpenCV library, it refers to practical application of them a finally compares different provided trained files.
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Audio Interface for Signal Procesor Using IEEE 1394 Bus
Staroň, Martin ; Přinosil, Jiří (referee) ; Schimmel, Jiří (advisor)
The scope of bachelor’s thesis is a design of the connection between the Freescale digital signal processor DSP56300 family and the DFM Audio DICE II iKit interface by way of the TDM bus. The DICE II iKit interface uses serial IEEE1394 FireWire bus that transmits an audio stream from a host computer. This signal receives the DICE II iKit interface that converts audio data from IEEE1394 FireWire to the TDM bus. The signal processor that process the sended audio data in a real time is connected to this TDM bus. The theoretical part of this work describes the theory of the digital signal processor, in detail DSP56300 Freescale family. After that there is a basic specification of the IEEE1394 FireWire bus. The theoretical part of this bachelor‘s thesis is ended by a description the TDM bus, the I2S interface and the AudifiedDSP Solution system. A connection of the signal processor and the DICE II interface was solved in the practical part, included the debbuging and the operating of the hadle subroutine for the duplex communication. The results of this thesis is might utilise for the duplex communication between the signal processor and aplication software working on the host computer.
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Android application for subjective evaluation of video-sequences
Štarha, Dominik ; Přinosil, Jiří (referee) ; Číka, Petr (advisor)
This semestral thesis is focused on a group of four actually used video codecs, namely H.264, HEVC, VP8, VP9. The main objective is to decide on the basis of an evaluation by volunteers which one is the best suitable for video compression. The first part of thesis contains theoretical aspect od the issue. This includes a discussion about the the tested codecs, Android operating system description, performance of the Android Studio software and last but not least, introduction to the assessment methods, used to evaluate video quality, to guarantee the objectivity of the results. The secont part of thesis deals with the implementation of the testing procedure and following evaluation of the data obtained by the assessment.
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Detection of security aids in image signal
Burdík, Vojtěch ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work is devoted to the relatively new field of computer – computer vision. It focuses on the recognition of people, positioning and colour detection of clothing placed on person. The aim is to build an algorithm that would be able to locate the person in the picture and would make colours tests of clothing and helmets. For image processing were used OpenCV library functions and from algorithms was compiled program solving this problem. The output of the program is the answer, what colour is person at stated locations wearing, and if clothing and helmet are the same colour, the person is evaluated as properly dressed. The resulting program is then disassembled and parts of the code are in detail described in this work. There is explained how to use correctly each OpenCV function used in program.
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Generation of Sound from Images
Brada, Tomáš ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This thesis deals with different kinds of converting image data (two-dimensional discrete signal) to sound data (one-dimensional discrete signal). Implemented algorithms are using knowledge of music theory, properties of human hearing and basic techniques of 1D and 2D signal processing as Fourier transform and modulating frequency spectrum via high-pass and low-pass filter.
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