Optic nerve head and macula are important structures in fundus images. Detection and measurement plays crucial role in several diagnosis methods of optic disease. This work is focused on the detection of the central point of macula and optic nerve head, where the inner border is detected too. There are many methods for extracting this structure in retinal images. Due to the unique properties of each acquisition technique, a single generally acknowledged detection algorithm does not exist. The whole detection process is described from preprocessing through segmentation towards postprocessing. Presented methods are based on the combination of correlation techniques, Hough transform, active contours and morphological operations. The detected contours of the optic nerve head are evaluated and quantitatively compared with the contour drawn by experienced ophthalmologist. The master thesis contains quantity of images that help to describe detection methods.

This work deals with the method for analysis of one-port microstrip circuits which is called as contour-integral method. The general procedure for evaluating of important parameters concerning the analysis of microstrip antennas is given. Next, the geometrical parameters necessary for the calculation of elements in U and H matrices are numerically solved. With the help of these matrices, the input impedance or the reflection coefficient can be easily found.

The master’s thesis deals with the design and realization of a program that is able to find the shortest route in the tourist map between selected points. The user can select the type of hiking trail. Application also generates terrain heightmap from contour lines and path elevation profile.

This master’s thesis is focused on digital image analysis of mitotic chromosomes. It deals with the design of the processing of digital images - from image preprocessing to clasification of each chromosomes, including testing on a set of images. This work introduces used cytogenetic methods, that are used to visualize chromosomes. In its practical part describes morphology operations and clasification procedure. Classification of the chomosomes was divided into 5 groups (A-G). All algorithms were created in the MATLAB program.

This thesis focuses on advanced methods of detecting contours of the cardiac cells and measuring their contraction. The theoretical section describes the types of confocal microscopes, which are used for capturing biological samples. The following chapter is devoted to the methods of cardiac cells segmentation, where we are introduced to the generally applied approaches. The most widely spread methods of segmentation are active contours and mathematical morphology, which are the crucial topics of this thesis. Thanks to the those methods we are able in the visual data to accurately detect required elements and measure their surface chnage in time. Acquired theoretical knowledge leads us to the practical realization of the methods in MATLAB.

The aim of this thesis is to create map of cave Výpustek surrounding enviroment. It is going to be complementary map documentation to existing map documentation made by the other students of VUT Brno. These documentations will be joined together and create one relief covering terain above the cave. The work began with building our own traverse and measuring detailed points. The result is topographical and hypsographical determination of the locality expressed numerically and topographically too. Another task was to measure and represent some profiles of main halls and passages of the cave. Intention is to connect underground space with the surface. Surveying network of points built previously inside the cave was used for measurements.

This thesis deals with segmentation of tennis player´s body parts for analysis its motion. Testing code was written in C++ with use of OpenCV library. Some image processing techniques such as thresholding, background subtraction or finding the largest contours were implemented. There was used a linear triangulation technique for calculating the 3D coordinates of segmented points.

Dans le cadre de systèmes d’aide à la conduite, nous avons contribué aux approches de stéréovision pour l’extraction de contour, la mise en correspondance des images stéréoscopiques et la détection de véhicules. L’extraction de contour réalisée est basée sur le concept declivity line que nous avons proposé. La declivity line est construite en liant des déclivités selon leur position relative et similarité d’intensité. L’extraction de contour est obtenue en filtrant les declivity lines construites basées sur leurs caractéristiques. Les résultats expérimentaux montrent que la declivity lines méthode extrait plus de l’informations utiles comparées à l’opérateur déclivité qui les a filtrées. Des points de contour sont ensuite mis en correspondance en utilisant la programmation dynamique et les caractéristiques de declivity lines pour réduire le nombre de faux appariements. Dans notre méthode de mise en correspondance, la declivity lines contribue à la reconstruction détaillée de la scène 3D. Finalement, la caractéristique symétrie des véhicules sont exploitées comme critère pour la détection de véhicule. Pour ce faire, nous étendons le concept de carte de symétrie monoculaire à la stéréovision. En conséquence, en effectuant la détection de véhicule sur la carte de disparité, une carte de symétrie (axe; largeur; disparity) est construite au lieu d’une carte de symétrie (axe; largeur). Dans notre concept, des obstacles sont examinés à différentes profondeurs pour éviter la perturbation de la scène complexe dont le concept monoculaire souffre. / In the framework of driving assistance systems, we contributed to stereo vision approaches for edge extraction, matching of stereoscopic pair of images and vehicles detection. Edge extraction is performed based on the concept of declivity line we introduced. Declivity line is constructed by connecting declivities according to their relative position and intensity similarity. Edge extraction is obtained by filtering constructed declivity lines based on their characteristics. Experimental results show that declivity line method extracts additional useful information compared to declivity operator which filtered them out. Edge points of declivity lines are then matched using dynamic programming, and characteristics of declivity line reduce the number of false matching. In our matching method, declivity line contributes to detailed reconstruction of 3D scene. Finally, symmetrical characteristic of vehicles are exploited as a criterion for their detection. To do so, we extend the monocular concept of symmetry map to stereo concept. Consequently, by performing vehicle detection on disparity map, a (axis; width; disparity) symmetry map is constructed instead of an (axis; width) symmetry map. In our stereo concept, obstacles are examined at different depths thus avoiding disturbance of complex scene from which monocular concept suffers.

No description available.

Context : Air being the free source is used in different ways commercially. In earlier days windmills generate power, water, and electricity. The excessive establishment of windmills for commercial purposes affected avifauna. Most of the birds lost their lives due to collisions with windmills. Turbines used to generate power near airports are also one of the causes for the extinction of birdlife. According to a survey in 2011 in Canada a total of 23,300 bird deaths were caused by wind turbines and also it is estimated that the number of deaths would increase to 2,33,000 in the following 10-15 years. Objectives : The main objective of this thesis is to find a suitable software solution to detect the birds on a series of grayscale images in real-time and in minimum full HD resolution with at least a 15 FPS rate. User-Driven Design Methodology is used for developing, tools are Python and Open-CV. Methods : In this research, a system is designed to detect the bird in an HD Video. Possible methods that can be considered are convolutional neural networks (CNN), vision based detection with background subtraction, contour detection and confusion matrix classification. These methods detect birds in raw images and with help of a classifier make it possible to see the bird in desired pixels with full resolution. We will investigate a bird classification method consisting of two steps, background subtraction, and then object classification. Background subtraction is a fundamental method to extract moving objects from a fixed background. For classification, we will use the YOLO v3 model version for object classification. Results : The project is expected to result in a system design and prototype for the bird identification on a grayscale video stream in at least full HD resolution in a minimum of 15 FPS. The bird should be distinguished from other moving objects like wind turbine blades, trees, or clouds. The proposed solution should identify up to 5 birds simultaneously. Conclusion : After completing each step and arriving at the classification, the methods we have tried, such as Haar Cascades and mobile-net SSD, were not providing us with the desired results. So we opted to use YOLO v3, which had the best accuracy in classifying different objects. By using the YOLO v3 classifier, we have detected the bird with 95% accuracy, blades with 90% accuracy, clouds with 80% accuracy, trees with 70% accuracy. Moreover, we conclude that there is a need for further empirical validation of the models in full-scale industry trials.