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object matching
Mišta, Petr ; Petyovský, Petr (referee) ; Richter, Miloslav (advisor)
Detection of objects based on color is not commonly used method of computer vision. There are many methods thats deals with the detection of significant points, but the color information has been omitted. The goal of this thesis is to design method of the detection significant color image areas and these areas match up with areas detected in another image. I analyzed features of detectors required to identify the reciprocal correspondence of images, defined the color significance concept, described basic color models and their properties, and a design of statistically compiled data - based method was described. Algorithms for the detection of color use color models RGB and HSV. Correspondence of areas detected in different images is performedy Kohonen neural network. The first input vector can teach Kohonen neural network and the second vector is classified by this network. To remove erroneous classifications RANSAC method is used. As a result, the method can be used for basic and rapid determination of correspondence between images, or to speed up commonly used methods for detection of significant points. At the end of the thesis are presented programs, showing functionality and options of design methods. The designed algorithms have been developed in MATLAB.
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Long-term Analysis of Ultrasound Video Sequences Using Interest Point Detectors
Zukal, Martin ; Závodná, Eva (referee) ; Papež,, Václav (referee) ; Říha, Kamil (advisor)
This doctoral thesis deals with the analysis of ultrasound (US) video sequences. It specifically focuses on long-term tracking of the common carotid artery (CCA) in transversal section and measurement of its geometric parameters in a sequence of US images. The design and implementation of a system for automatic tracking of the artery is described in this thesis. The proposed system utilizes Viola-Jones detector and Hough transform to localize the artery in the image. Interest points are detected in the area of the artery wall. These points are then tracked using optical flow. The proposed system comprises a number of innovative methods which allow to perform accurate long-term measurement of parameters of CCA and store the results. A novel mathematical model describing the movement of CCA in transversal section during a cardiac cycle is defined afterwards taking the influence of breathing into consideration. A number of artificial sequences of US images based on this model have been created. These sequences were consequently used to evaluate the accuracy of the proposed system in terms of measuring the parameters of CCA. The sequences are unique because of their length which makes them suitable for evaluation of tracking accuracy even in long video sequences.
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Interest Points Tracking in Video Sequence of Non-stationary Camera
Studený, Pavel ; Davídek, Daniel (referee) ; Horák, Karel (advisor)
The thesis deals with the issue of tracking feature points earned from videosequences of hand helded camera. The work is focused on the case of moving camera and static background, and events that are associated with this case and can occur. There is studied the movement of the camera, which is given its direction and speed. The aim of this work is the election and the subsequent implementation of three fundamentally different methods suitable for tracking feature points in case of moving camera and their comparison according to set criteria. On the basis of comparison will be under pre-defined conditions chosen algorithm that is best able to deal with tracing these points.
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Minidarpa robot - visual navigation
Groulík, Tomáš ; Burian, František (referee) ; Kopečný, Lukáš (advisor)
Master`s thesis is focused on mobile robotics and computer vision. There is briefly introduced a library of functions for image processing OpenCV. Then it deals with image processing and navigation of mobile robots using image data. There are described segmentation methods and methods for navigating through feature points.
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Detection of Corresponding Points in Images
Ptašek, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
Bachelor thesis is concerned with detection of corresponding points in two digital images. It summarises and describes basic, new and modern methods of detection of interest points. It also describes methods for determinating equivalence of image parts. Work itself includes design of application and describes implementation of corresponding points detector based on segmentation method MSER. Application was written in C programming language and uses Open CV graphic library under Windows XP operating system. Results that summarise characteristics of detector illustrate potential of chosen methods.
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Facial features recognition of unknown persons
Bartončík, Michal ; Babinec, Tomáš (referee) ; Horák, Karel (advisor)
This paper describes the various components and phases of the search and recognition of facial expressions of unknown persons. They are presented here as well as possible solutions and methods of addressing each phase of the project. My master’s thesis is designed to recognize facial expressions of unknown persons. For this thesis, I was lent industrial video camera, computer, and place in a laboratory. Furthermore, we introduce the color spaces and their use. From the lead representatives selects the most appropriate assistance for the use of Matlab and the proposed algorithm. After finding a suitable color space segments skin color in the image. The skin, however, surrounds the entire body and so need to be found, the separated parts of the image representing the color of skin, a face. Once you find a face is needed to find relevant points for the identification subsequent deformation to definition of facial expressions. We define here the actual muscle movements in different expressions.
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Corners Detection in Images
Hýna, Petr ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
Corner detection is important because of getting a subset of points from the set of all picture points. This subset is used for enquiry into relations of images. Searching of such relations is then less time and memory consuming. The text is about corner detection with focus on method Harris Stephens. The implementation is part of MDSTk and it is written in C/C++ with use of MDSTk's libraries.
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Finding of known object in a series of digital images
Bednařík, Jan ; Hasmanda, Martin (referee) ; Číka, Petr (advisor)
The aim of the thesis is detection of a known object in series of pictures. Detection is divided into two methods. First method is based on edge and color detection and comparison. Edge detection is based on detection using both Gradient and Laplacian, so on the first-order and the second-order derivative. Sobel operators were used as well as Laplacian of gaussian method. Thresholding is also used as well as autothreshold calculation. There are two variants of color detection considered in the thesis, direct color comparison and detection based on interest color search. The second part of the thesis is based on interested point detection using a modified SURF method to detect a known object in series of pictures.
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Interest Points Tracking in Video Sequence of Non-stationary Camera
Studený, Pavel ; Davídek, Daniel (referee) ; Horák, Karel (advisor)
The thesis deals with the issue of tracking feature points earned from videosequences of hand helded camera. The work is focused on the case of moving camera and static background, and events that are associated with this case and can occur. There is studied the movement of the camera, which is given its direction and speed. The aim of this work is the election and the subsequent implementation of three fundamentally different methods suitable for tracking feature points in case of moving camera and their comparison according to set criteria. On the basis of comparison will be under pre-defined conditions chosen algorithm that is best able to deal with tracing these points.
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Corners Detection in Images
Hýna, Petr ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
Corner detection is important because of getting a subset of points from the set of all picture points. This subset is used for enquiry into relations of images. Searching of such relations is then less time and memory consuming. The text is about corner detection with focus on method Harris Stephens. The implementation is part of MDSTk and it is written in C/C++ with use of MDSTk's libraries.
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