My master's thesis deals with the different techniques used in fingerprints processing for identifying fingerprints. Using the software tool Visual C++ and functions of OpenCV library I programmed a separate application, that is able to select from a database of fingerprints the most consistent with a comparative fingerprint images, even when they are mutually shifted in the direction of axes X and Y. The next step in my program is to gather the edges of the fingerprint image. Those obtained using Canny edge detector. Furthermore, getting the contours of the image edges. To determine, whether the contours are the same, just compare some characteristic points of contours. Next I use a histogram function to determine the number of points for approximation of contours and evaluating compliance fingerprints. Since the processing of the input fingerprint image (or rather the approximation of the contour points) remains in the picture as black (background) and red (the approximation of the contour points), this means, that zero and the last element of the histogram represent the number of black and red points. Comparison is in percentage and is obtained by subtracting the approximated points of contours image from the original fingerprint image of approximated contour points of matched fingerprints. It determined, what percentage of red points have disappeared, so as to match two fingerprint images. If on the resulting figure is not left neither a red point, that corresponds to 100% of the fingerprints Compliance.

This thesis adresses designing a device that detects lane departure of a vehicle via a video feed from a camera module. This device is intended to be attached onto the windshield of the vehicle. The initial part of the thesis will cover the current methods of lane departure detection through a video feed. In the following part the selection of suitable hardware, specifically the latest model of a Raspberry Pi, has been made. Afterwards a suitable container for the aforementioned hardware has been designed and created using a 3D printer. Subsequently an appropriate LDWS algorithm is chosen and designed. In the next part, the range and parameters of a testing database through which the proper functionality of the device will be tested on are chosen. The final part of the thesis contains evaluation of the success rate of detection via the acquired database.

This diploma thesis deals with the issue of the recognition of road signs in the video sequence. Such systems increase the traffic safety and are implemented by major car factories in the manufactured cars (Opel, BMW). First, the motivation for the utilisation of these systems is presented, followed by the survey of the current state of the art methods. Finally, a specific road-sign detection method is chosen and described in detail. The method uses advanced techniques of signal processing. Segmentation method in color space is used for sign detection and subsequent classification is accomplished by linear classification with optional use of PCA method. In addition, the method contains the prediction of road sign positions based on Kalman filtering. Implemented system yields relatively accurate results and overall analysis and discussion is enclosed.

The aim of this thesis is to examine the possibility of a court detection program for sports videos that can identify the court even when some important elements are not visible. The study will also analyze what external factors may impact the program's accuracy in detecting all relevant elements.  These questions are answered through a combination of computer vision techniques and algorithms. The study utilizes Design Science Research (DSR) as its research methodology to develop an artifact. A dataset of padel sports videos are evaluated to measure the artifacts accuracy. The artifact utilizes multiple computer vision techniques from the OpenCV library to detect relevant lines and edges and project them onto the frame using a predetermined court model as reference.  The findings indicated that the developed artifact demonstrated a relatively consistent level of accuracy in court detection across multiple courts, whenever a detection was made. However, the frequency of successful detections exhibited some inconsistency. The research also found that external factors did not significantly influence the accuracy of court detection, yet they posed challenges to the program's overall consistency.

The thesis deals with design of a program for entering various types of geometric objects in an image for the purpose of their further processing. The program should also contain algorithms to ease object entering (e.g. refining manually entered object position). In the first part there is a brief description of the computer vision and its basic methods used in the work as well as introduction of the OpenCV image processing library. The following part describes three types of geometric primitives that are implemented for now. Because the output of the program is in universal XML format, there is short chapter about the XML. After that, there are summarized some methods for searching of parametric description of geometric primitives in an image. The final chapter describes the proposed system and evaluates possibility and suitability of its usage for various types of images.

This thesis presents the Deriche edge detector as an interesting alternative to the commonly used edge detectors. The Deriche edge detector's design is presented to the reader as well as its strengths and weaknesses. Performance issues of the Deriche edge detector are described in comparison with the Canny edge detector together with recommendations for using the Deriche detector. Finally, edge detection quality of the Deriche edge detector is compared to the Canny edge detector using robust subjective evaluation method.

This thesis deals with curve detection in images. First, current methods used in this area of image processing are summarized and described. Main topic of this thesis is a comparison of methods of parametric curve detection, such as Hough transformation and RANSAC-based methods. These methods are compared according to several criteria which are the most important for precise edge detection.

This work outlines a method of detection of the papillary line width in fingerprints. This method is one of the possible methods of liveness detection. The first part of the work with deals defining of the fingerprint, attacks on today's systems and possibilities to improve security. The next section detection describes of the papillary line width. During the process of resolving, the first thing to do was to start operation of the scanning device and to read the database for tests and experiments. An independent application was created on this purpose. Further, there were projected methods for detection and measuring of the papillary line width. Use of the Canny edge detector with the Sobel operator and the Gaussian filter proved the best. Then, there is described implementation of individual methods. The next part of the work describes and assesses the results of the tests. The last chapter summarizes the work and proposes further possibilities of development.

This paper concerns methods of verification of person's signature and handwriting. Some of commonly used techniques are resumed and described with related literature being referred. Next aim of this work is design and implementation of a simple handwriting verification application. Application is based on edge detection and comparison of a set of structural and statistical features. As a support classification tool a SVM classifier of the LIBSVM software is employed. The Application is written in C language using OpenCV graphics library. Testing and training set was extracted from samples found in the IAM Handwriting Database. Application was created and tested in the Windows XP operating system.

In this work is describe anatomy and physiology of the cornea. The following are the primary non-inflamatory degeneration of the cornea. Then describe the physical principles diagnostic devices for cornea – keratometer, pachymeter, Michelson interferometr and optical coherence tomography (OCT). At the end of the theoretical introduction is describes the principle of laser correction surgery – LASIK. The practical part is divided into two main objectives. The first task is propose an algorithm for automatic detection of corneal surface and then calculation of corneal thickness and size of the chamber angle in Matlab. The aim of the second task is image flap analysis for boundary detection.