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Segmentation techniques for image processing
Bajgar, Aleš ; Číka, Petr (referee) ; Říha, Kamil (advisor)
For image segmentation are used several methods. Good results can be achieved by the correct choice of method. Best results are using more methods together. Methods such as thresholding, the search area or methods founded on edge detection in an image. We can use different filters for noise removal. For example Gaussian, median, etc. Lowpass filter can also be used. Image segmentation Mean Shift, K-mean, watershed and pyramid segmentation performed by using methods from the OpenCV library.
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Techniques Used for Image Smoothing, Blurring and Sharpening
Kubínek, Jiří ; Šilhavá, Jana (referee) ; Venera, Jiří (advisor)
This work is dedicated to methods used for digital image editing. It defines fundamental terms for this work as color space or noise. Above all, it analyses methods allowing image sharpening and blurring. It describes some of the most known algorithms from the theoretical point of view, but also introduces their implementation in C programming language. There are compared according to time complexity. The purpose of this work is to introduce digital image filtering and demonstrate elementary procedures used for their implementation.
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Static image enhancement using wavelet transform
Candrák, Matúš ; Rajmic, Pavel (referee) ; Smékal, Zdeněk (advisor)
In tomography and ultrasound signal processing, there is the noise build-up into the processing. Bachelor's thesis deals with static images highlighting, with denoising using wavelet transformation and edge detection with basic operators. This work describes some types of wavelts used for denoising of image and basic operators for edge detection in the image. The last part deals with a particular application for image processing, which was created in MATLAB.
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Polygonal Models Smoothing
Nečas, Ondřej ; Herout, Adam (referee) ; Kršek, Přemysl (advisor)
The result of digitalization 3d surface is affected by many factors. After digitalization can on the surface emerge some unwanted artefacts. The differences from original are caused by resolution of the device or its limited precision. For elimination of this artefact exists many smoothing algorithms, but we want to choose that which best suits this purpose. So it is useful to know their limits and characteristics.
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Techniques Used for Image Smoothing, Blurring and Sharpening
Kubínek, Jiří ; Šilhavá, Jana (referee) ; Venera, Jiří (advisor)
This work is dedicated to methods used for digital image editing. It defines fundamental terms for this work as color space or noise. Above all, it analyses methods allowing image sharpening and blurring. It describes some of the most known algorithms from the theoretical point of view, but also introduces their implementation in C programming language. There are compared according to time complexity. The purpose of this work is to introduce digital image filtering and demonstrate elementary procedures used for their implementation.
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Implementation of Ford-Fulkerson Algorithm
Makovský, Benjamin ; Rychnovský, Lukáš (referee) ; Masopust, Tomáš (advisor)
This work describes the design of the graphic implementation of the Ford-Fulkerson Algorithm for searching the maximum flow and the minimal cut in the network. It contains a brief introduction with the theory of the graphs and the flows in the networks, it describes the principle of the Ford-Fulkerson Algorithm. The object design representing the graph in the program is cited, the drawing of the graph by the program and the creation of the graphic user interface of the application is described. The final program is worked up as a Java applet which is placed at the public internet pages www.ffaplikace.php5.cz.
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Techniques Used for Image Blurring and Sharpening
Lichý, Stanislav ; Juránek, Roman (referee) ; Venera, Jiří (advisor)
This bachelor's thesis deals with methods of digital image filtering. First of all, it contains basic notions necessary to understand problems, such as digital image, pixel, color spaces, noise and noise types. Secondly, important algorithms of image sharpening and noise reduction are described. Then, algorithms working principles are explained. Achieved results are analyzed together with a discussion about algorithms suitability and their time complexity. Lastly, selected algorithms are implemented by C++ programming language, using an open source library OpenCV.
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