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Methods of image dithering
Pelc, Lukáš ; Křupka, Aleš (referee) ; Rajmic, Pavel (advisor)
Master’s thesis discusses methods for dithering image. The basis is the explanation of the theory of digital images, color models, color depth and color range. Followed by the dismantling of the basic dithering methods which are a thresholding method, a random and matrix diffusion. Discussed are advanced methods of dithering with error distribution, bee with best known method Floyd-Steinberg. Included is a comparison of different methods including subjective comparison using a questionnaire. Program part is JAVA applet that shows the possibility of generating images using various dithering methods.
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Application of optimisation methods for MRI data segmentation
Olešová, Kristína ; Mézl, Martin (referee) ; Chmelík, Jiří (advisor)
This thesis deals with a segmentation of brain tissues from MRI image data and its implementation in MATLAB. Segmentation problematic is described with attention to formulating segmentation as optimization problem and segmentation of given images with different metaheuristic algorithm consequently. This approach was chosen due to information from last specialized publications, where it was accentuated for its fast computational speed and universality. This thesis tries to prove this statement with segmentation of brain images with brain tumours that have different types, number, stage of illness and phase of therapy.
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ECG signals compression
Botlová, Simona ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
This bachelor thesis deals with the compression of ECG signals using wavelet transform and run length encoding. The principles of electrocardiography, compression methods, wavelet transform and run length encoding are described in this thesis. There was created a program to compress and decompress ECG signals in MATLAB interface. The wavelet transform settings and their influence on compress ratio and percentage root mean square difference were tested. Subsequently, the appropriate adjustment of algoritm was found and it was used on CSE database compression.
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Wavelet transform based object detector
Mikuš, Ondřej ; Průša, Zdeněk (referee) ; Rajmic, Pavel (advisor)
This thesis deals with applying methods on object detection in image. Separation of objects off the background is often needed during the image processing. It isolates the region of interest that can be worked with. The main purpose of this paper is the explanation of principles of pre-processing and segmentation of image, resulting in object detection using the wavelet transformation. This wavelet transformation is described more in detail, because it is the base of the primary used method. In the practical part of this thesis the main method was implemented to MATLAB environment and tested on set of images. The method was tested for robustness against noise and blur of image. It was compared with commonly used methods, using the edge detectors and thresholding. A simulation program was created for comparison of methods efficiency, including user interface.
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Neural Network Based Edge Detection
Jamborová, Soňa ; Grézl, František (referee) ; Švub, Miroslav (advisor)
This work is about suggestion and implementation of the software for detection of edges in images using neurons network. It defines basic terms for this topic and focusing mainly at preperation imaging imformation for detection using nerons network. Describing and comparing different aproachings for using implemented software on synthetic and real set of images, including experiments.
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ECG Signal Compression Based on Wavelet Transform
Ondra, Josef ; Hrubeš, Jan (referee) ; Kozumplík, Jiří (advisor)
Signal compression is daily-used tool for memory capacities reduction and for fast data communication. Methods based on wavelet transform seem to be very effective nowadays. Signal decomposition with a suitable bank filters following with coefficients quantization represents one of the available technique. After packing quantized coefficients into one sequence, run length coding together with Huffman coding are implemented. This thesis focuses on compression effectiveness for the different wavelet transform and quantization settings.
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Microscope Image Processing
Janda, Ondřej ; Ošmera, Pavel (referee) ; Matoušek, Radomil (advisor)
This diploma thesis deals with image processing of microbiological data. Firstly the brief introduction to biological basics is given. Secondly we take focus on basic and used image processing methods. Integral part of this thesis is working application witch uses image processing methods on input data. Creating user interface for this application is also part of this work. Documentation is provided.
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Recognition of Objects in Pictures
Nedoma, David ; Samek, Jan (referee) ; Zbořil, František (advisor)
This thesis is about solving a problem of recognition of objects in pictures. The aim was to create a program that will be able to recognize objects in an image. Describes progressively step by step processing of image data. Shortly describes preprocessing of image, after that describes in detail segmentation, description of segmented data and classification of objects. Describes algorithms and methods that are applicable for each step.
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Simple wavelet filter of ECG signals
Doležel, Jiří ; Ronzhina, Marina (referee) ; Smital, Lukáš (advisor)
The work deals with wavelet transfom and its possibilities of using it for elimination muscle noise from ECG signals. The first part of this thesis describes basic properties of ECG signal, the most common types of noise and describes basic types of wavelet transform, which are used for filtering the signals. Others parts describe a process of ECG signals wavelet filter design and afterwards the most appropriate setting are described. Finally results of filtration are evaluated, based on improved SNR, and compared with other author’s results.
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Greyscale to binary image conversion
Růžička, Kamil ; Horák, Karel (referee) ; Richter, Miloslav (advisor)
In the first part of the bachelor’s thesis are described the basic terms in obtaining and description of a digital image. The next part describes the theory about possibilities of image processing, which are essential for the correct separation of the text from the background, and thus for the correct conversion grayscale image to binary image. Then was performed the analysis of the task with the preparation of data for image processing. Then were applied different methods for converting grayscale to binary images and it was compiled user application. The final step is to evaluate the practical realization of the conversion, the subjective testing of respondents and objektive testing with the OCR software.
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