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Algorithms for composing a puzzle
Šarda, Petr ; Číp, Pavel (referee) ; Horák, Karel (advisor)
This diploma thesis deals with constructing of algorithms of consisting a puzzle and suggesting of the workplace for its imaging. There are studied two methods of forming a puzlle. First method is forming of the puzzle with a known pattern. For this method is used the Harris operator and the correlation. In the second method is the puzzle formed without a pattern. Fot this method is used the correlation. In the last part there is a mutual evaluation of these two methods.
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Interest-Point Detection on CUDA
Ryba, Jan ; Řezníček, Ivo (referee) ; Herout, Adam (advisor)
Corner point detection is one of many functions used in computer vision for tasks such as tracking, detecting objects, comparing images and much more. Many of the algorithms are complex and require a lot of CPU time. This is where the CUDA platform comes in. CUDA kernels run parallely on graphic accelerators can rapidly decrease time needed for execution, allowing even these complex calculations to work in real time or even better. Text focuces on Moravec and Harris corner detection algorithms and their effective implementation on CUDA. Examination of potetntial and performance of CUDA platform is also importatnt.
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Searching for Points of Interest in Raster Image
Kaněčka, Petr ; Sumec, Stanislav (referee) ; Herout, Adam (advisor)
This document deals with an image points of interest detection possibilities, especially corner detectors. Many applications which are interested in computer vision needs these points as their necessary step in the image processing. It describes the reasons why it is so useful to find these points and shows some basic methods to find them. There are compared features of these methods at the end.
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Region Detectors and Descriptors in Image
Žilka, Filip ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master’s thesis deals with an important part of computer vision field. Main focus of this thesis is on feature detectors and descriptors in an image. Throughout the thesis the simplest feature detectors like Moravec detector will be presented, building up to more complex detectors like MSER or FAST. The purpose of feature descriptors is in a mathematical description of these points. We begin with the oldest ones like SIFT and move on to newest and best performing descriptors like FREAK or ORB. The major objective of the thesis is comparison of presented methods on licence plate localization task.
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Region Detectors and Descriptors in Image
Žilka, Filip ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master’s thesis deals with an important part of computer vision field. Main focus of this thesis is on feature detectors and descriptors in an image. Throughout the thesis the simplest feature detectors like Moravec detector will be presented, building up to more complex detectors like MSER or FAST. The purpose of feature descriptors is in a mathematical description of these points. We begin with the oldest ones like SIFT and move on to newest and best performing descriptors like FREAK or ORB. The major objective of the thesis is comparison of presented methods on licence plate localization task.
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Interest-Point Detection on CUDA
Ryba, Jan ; Řezníček, Ivo (referee) ; Herout, Adam (advisor)
Corner point detection is one of many functions used in computer vision for tasks such as tracking, detecting objects, comparing images and much more. Many of the algorithms are complex and require a lot of CPU time. This is where the CUDA platform comes in. CUDA kernels run parallely on graphic accelerators can rapidly decrease time needed for execution, allowing even these complex calculations to work in real time or even better. Text focuces on Moravec and Harris corner detection algorithms and their effective implementation on CUDA. Examination of potetntial and performance of CUDA platform is also importatnt.
|
|
|
Searching for Points of Interest in Raster Image
Kaněčka, Petr ; Sumec, Stanislav (referee) ; Herout, Adam (advisor)
This document deals with an image points of interest detection possibilities, especially corner detectors. Many applications which are interested in computer vision needs these points as their necessary step in the image processing. It describes the reasons why it is so useful to find these points and shows some basic methods to find them. There are compared features of these methods at the end.
|
|
|
Algorithms for composing a puzzle
Šarda, Petr ; Číp, Pavel (referee) ; Horák, Karel (advisor)
This diploma thesis deals with constructing of algorithms of consisting a puzzle and suggesting of the workplace for its imaging. There are studied two methods of forming a puzlle. First method is forming of the puzzle with a known pattern. For this method is used the Harris operator and the correlation. In the second method is the puzzle formed without a pattern. Fot this method is used the correlation. In the last part there is a mutual evaluation of these two methods.
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