National Repository of Grey Literature 16 records found  previous11 - 16  jump to record: Search took 0.01 seconds. 
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.
Canny's Operator and Other Useful Edge Detectors
Janda, Miloš ; Juránek, Roman (referee) ; Venera, Jiří (advisor)
This work introduces main approaches for digital image processing and defines fundamental terms for successful understanding. Main aim is description of several suitable methods used in digital image pre-processing, methods for edge detection and consequent post-processing of these. The final goal of this work is effective implementation and complex comparison of methods for edge detection.
Neural Network Based Edge Detection
Jamborová, Soňa ; Grézl, František (referee) ; Švub, Miroslav (advisor)
This work is about suggestion and implementation of the software for detection of edges in images using neurons network. It defines basic terms for this topic and focusing mainly at preperation imaging imformation for detection using nerons network. Describing and comparing different aproachings for using implemented software on synthetic and real set of images,  including experiments.
Neural Network Based Edge Detection
Janda, Miloš ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
Aim of this thesis is description of neural network based edge detection methods that are substitute for classic methods of detection using edge operators. First chapters generally discussed the issues of image processing, edge detection and neural networks. The objective of the main part is to show process of generating synthetic images, extracting training datasets and discussing variants of suitable topologies of neural networks for purpose of edge detection. The last part of the thesis is dedicated to evaluating and measuring accuracy values of neural network.
Moving Objects Detection in Video Sequences
Havelka, Jan ; Ševcovic, Jiří (referee) ; Španěl, Michal (advisor)
The topic of this thesis is the recognition and detection of moving object and persons in video sequence and in the static image. Designed application uses the combination of background model for movement detection, histograms of oriented gradients method for person recognition and Lucas-Kanade method for object tracking.
Neural Network Based Image Segmentation
Jamborová, Soňa ; Řezníček, Ivo (referee) ; Žák, Pavel (advisor)
This work is about suggestion of the software for neural network based image segmentation. It defines basic terms for this topics. It is focusing mainly at preperation imaging information for image segmentation using neural network. It describes and compares different aproaches for image segmentation.

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