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Application for Processing of a Photographed Text
Genčúr, Martin ; Rozman, Jaroslav (referee) ; Grulich, Lukáš (advisor)
This work introduces main approches for converting a photographed text into black and white form. It analyses particular methods being used for this task. Following part describes implementation of the application performing a conversion. The program is tested with suitable data (coloured picture, a picture with various shades etc.) and illustrates the usability of the application. The thesis also contains an introduction to optical character recognition (OCR) and suggests potential ways of development of this application.
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Vein-Artery Segmentation of Blood Vessels in Retinal Images
Sedlář, Radek ; Kanich, Ondřej (referee) ; Kavetskyi, Andrii (advisor)
This work focuses on an introduction to the issue of segmentation of veins and arteries from retinal images. The work contains a comparison of the most used methods with their pros and cons. Furthermore, a proprietary method for segmentation and division into veins and arteries is proposed. The work also contains a detailed description of the implementation of the proposed method and a summary of their results.
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Company's Expantion into the Polish Market
Milerski, Tomáš ; Novotný, Tomáš (referee) ; Zich, Robert (advisor)
This thesis proposes the optimal measures to expand company's business by entering the Polish market. The actual solution is based on a thorough analysis of the local environment using standard and advanced methods of evaluation. Emphasis is placed on the quality of data and their correct interpretation. The thesis provides a comprehensive look at the situation on the market and proposes the most appropriate method of implementation, taking into account all the risks and opportunities, which the company may encounter during the expansion.
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Precise segmentation of image data
Svoboda, Jan ; Marcoň, Petr (referee) ; Mikulka, Jan (advisor)
The concern of this thesis is a development of an extension module for 3D Slicer platform. The core of the module is an implementation of a Support Vector Machines classifier, which is used for segmentation of the vertebral column image data provided by the University Hospital Brno. One of the goals of the thesis was resampling and registration of these image sequences. CT volumes provided solid contrast and were used as a reference for gaining properly segmented groups of vertebrae. Due to the low quality of the MRI volumes image data, segmentation of MRI images was not completely succesful. The extension module scripted in Python language can be seen as a tool and can be used in the future for different datasets.
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Biometric fingerprint identification
Dašek, Filip ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
In biometrics we use distinctive physical features for identification and verification of identity. The most famous technique is identification by fingerprints. This technique use unique structure created by papillary lines for unambiguous identification. Thesis contains methods which were created throughout the years for analysis and adjustments of fingerprint. The algorithm is based on compairng two pairs of minitua and calculating transform matrix for correct alignment. Algorithm is tested on dataset created from LivDet databases. Performance of algorithm is represented by value EER which is compared with EERs of other algorithms tested in FVC 2006.
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Fingerprints Generator
Chaloupka, Radek ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
Algorithms for fingerprints recognition are already known for long time and there is also an effort for their best optimization. This master's thesis is dealing with an opposite approach, where the fingerprints are not being recognized, but are generated on the minutiae position basis. Such algorithm is then free of the minutiae detection from image and enhancements of fingerprints. Results of this work are the synthetic images generated according to few given parameters, especially minutiae.
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Degree of Parkinson's disease estimation based on acoustic analysis of speech
Ustohalová, Iveta ; Kiska, Tomáš (referee) ; Galáž, Zoltán (advisor)
The diploma thesis deals with the non-invasive analysis of progression of Parkinson´s disease using the acoustic analysis of speach. Hypokinetic dysarthria in connection with Parkinson´s disease as well as speech parameters are described in this work. Speech parameters are sorted according to the speech component they affect. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Based on obtained knowledge, in MATLAB development enviroment were created systém for UPDRS III scale estimation. The UPDRS III scale is based on subjective diagnosis given by the doctor. At first, one individual parameter is used for the UPDRS III scale value estimation. Then the feature selection using SFFS algorithm is applied to gain feature combination with minimal estimation errror. Attention i salso paid to correlation between individual symptoms and UPDSR III scale.
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Methods of Detection, Segmentation and Classification of Difficult to Define Bone Tumor Lesions in 3D CT Data
Chmelík, Jiří ; Flusser,, Jan (referee) ; Kozubek, Michal (referee) ; Jan, Jiří (advisor)
The aim of this work was the development of algorithms for detection segmentation and classification of difficult to define bone metastatic cancerous lesions from spinal CT image data. For this purpose, the patient database was created and annotated by medical experts. Successively, three methods were proposed and developed; the first of them is based on the reworking and combination of methods developed during the preceding project phase, the second method is a fast variant based on the fuzzy k-means cluster analysis, the third method uses modern machine learning algorithms, specifically deep learning of convolutional neural networks. Further, an approach that elaborates the results by a subsequent random forest based meta-analysis of detected lesion candidates was proposed. The achieved results were objectively evaluated and compared with results achieved by algorithms published by other authors. The evaluation was done by two objective methodologies, technical voxel-based and clinical object-based ones. The achieved results were subsequently evaluated and discussed.
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