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Detection of Boxes in Image
Soroka, Matej ; Bartl, Vojtěch (referee) ; Herout, Adam (advisor)
The aim of this work is to experiment and evaluate different approaches of computer vision with the aim of automatic detection of boxes-blocks in the image, for this purpose, approaches based on neural networks were used in the solution. Experiments were performed with classification using our own data set, classification using our own convolutional neural network, detection using a window, YOLO detector and in the last part a proposal for improvement using U-net and MirrorNet networks.
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Polygonal Mesh Segmentation
Švancár, Matúš ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This bachelor thesis analyzes and approaches the issue of segmentation of polygonal models. It presents a design of an interactive method inspired by the method described in the Interactive Mesh Segmentation Based on Feature Preserving Harmonic Field. The method uses graph-cut and is implemented as a web application. The application supports .obj and .stl file formats, allows the user to load a model, draw sketches representing foreground and background on the surface of the model, and to start segmentation. Once completed, the user can download the resulting models or continue segmenting with one of them.
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Volumetric Segmentation of Dental CT Data
Berezný, Matej ; Kodym, Oldřich (referee) ; Čadík, Martin (advisor)
The main goal of this work was to use neural networks for volumetric segmentation of dental CBCT data. As a byproducts, both new dataset including sparse and dense annotations and automatic preprocessing pipeline were produced. Additionally, the possibility of applying transfer learning and multi-phase training in order to improve segmentation results was tested. From the various tests that were carried out, conclusion can be drawn that both multi-phase training and transfer learning showed substantial improvement in dice score for both sparse and dense annotations compared to the baseline method.
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Analysis of neurite directionality
Plišková, Diana ; Čmiel, Vratislav (referee) ; Odstrčilík, Jan (advisor)
Práca je zameraná na navrhnutie vhodnej metódy analýzy smerovosti neuritov. Využité boli snímky neurónov z fluorescenčnej mikroskopie. Pred samotnou segmentáciou bolo potrebné snímky predspracovať, pričom sa postupne využila úprava kontrastu, ostrenie a adaptívna filtrácia pomocou Weinerovského filtru. Jednotlivé návrhy metód segmentácie pozostávali z prostého prahovania, narastaním oblastí a využitím morfologických operácií. Následná analýza smerovosti využívala smer gradientov v obraze. Navrhnutá metóda bola využitá aj ako klasifikátor, ktorý dokázal rozdeliť jednotlivé snímky do skupín podľa smeru rastu.
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Software for Biometric Recognition of a Human Eye Iris
Maruniak, Lukáš ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
In my thesis, I focus on the task of recognizing human iris from an image.In the beginning, the work deals with a question of biometrics, its importance and basic concepts, which are necessary for use in following text. Subsequently process of human Iris detection is described together with theory of evolution algorithms. In the implementation part, is described the design of implemented solution, which uses evolution algorithms, where is emphasis on correct pupil and iris boundary detection.
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Ultrasound Image Sequence Segmentation
Gallo, Vladimír ; Walek, Petr (referee) ; Mézl, Martin (advisor)
This paper presents basic principles of ultrasonography, review of different modes of medical ultrasound imaging, principle of contrast-enhanced ultrasonography and review of basic techniques of image segmentation. The individual methods based on edge detection and region growing were implemented in Matlab. The performance of algorithms were tested in each category using synthetic and phantom image data.
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Automatic speech recordings segmentation tool
Santa, Roman ; Zvončák, Vojtěch (referee) ; Kováč, Daniel (advisor)
Nástroj pre automatickú segmentáciu spracováva nahrávky reči a extrahuje hovorené slovo z nahrávok. Je dôležité, aby pokročilá analýza pracovala iba s rečovými časťami z nahrávky. Nástroj na segmentáciu má ulahčiť spracovanie nahrávok pre analýzu rozdielov medzi hláskami pacientov s parkinsonovou chorobou a tými zdravými. Cieľ tejto práce je navrhnúť a otestovať detektory reči s Google WebRTC detektorom a vybrať ten najvhodnejší detektor reči s minimálnym počtom chýb. Ďalej, vytvoriť nástroj na segmentáciu nahrávok a otestovať rozpoznávanie reči pomocou dynamic time warping. Bola použitá databáza poskytnutá laboratóriom pre analýzu mozgových ochorení. Obsahuje české a maďarské nahrávky s rovnakým počtom mužských a ženských pacientov a aj rovnakým počtom zdravých pacientov a pacientov s parkinsonovou chorobou. Najlepšie výsledky v testoch dosiahol detektor na základe energie reči. Nebol zistený žiaden rozdiel v presnosti detektoru pri spracovaní mužských a ženských nahrávok alebo nahrávok zdravých či chorých pacientov. Nahrávky s nízkym odstupom signálu od šumu boli náročnejšie na spracovanie s frekvenciou chýb od 12%. Na základe výsledkov, bol navrhnutý nový detektor pre spracovanie úplnej nahrávky. Na záver bol testovaný algoritmus pre rozpoznávanie podobnosti reči na základe melovských kepstrálnych koeficientov.
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Searching for Objects in Pictures
Motlík, Matúš ; Žák, Marek (referee) ; Zbořil, František (advisor)
This bachelor's thesis deals with solving the problem of searching simple objects in pictures. The aim was to create a program that will be able to search simple objects in grayscale images. In this theses are described progressively steps of image processing. There are described preprocessing of image, segmentation, description of segmented data, classification and searching for objects in image.
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