National Repository of Grey Literature 121 records found  beginprevious102 - 111next  jump to record: Search took 0.00 seconds. 
Raster Image Processing Using FPGA
Musil, Petr ; Kadlček, Filip (referee) ; Zemčík, Pavel (advisor)
This thesis describes the design and implementation of hardware unit to detect objects in the image. Design of unit is optimized for fast streaming processing. Object detection is performed by the trained classifiers using local image features. It describes a new technique for multi-scale detection. Detector used accelerating algorithm based on neighboring positions. The correct functionality of the detector is verified by simulation and part of a whole is implemented on development kit.
Learnable Evolution Model for Optimization (LEM)
Grunt, Pavel ; Vašíček, Zdeněk (referee) ; Schwarz, Josef (advisor)
My thesis is dealing with the Learnable Evolution Model (LEM), a new evolutionary method of optimization, which employs a classification algorithm. The optimization process is guided by a characteristics of differences between groups of high and low performance solutions in the population. In this thesis I introduce new variants of LEM using classification algorithm AdaBoost or SVM. The qualities of proposed LEM variants were validated in a series of experiments in static and dynamic enviroment. The results have shown that the metod has better results with smaller group sizes. When compared to the Estimation of Distribution Algorithm, the LEM variants achieve comparable or better values faster. However, the LEM variant which combined the AdaBoost approach with the SVM approach had the best overall performance.
Face Recognition
Vojáček, Cyril ; Chrápek, David (referee) ; Juránek, Roman (advisor)
This thesis is about face detection and recognition from video. Main emphasis is on computational speed, so it can be used for a real-time processing. Begining of this work focus on different approaches for detection and object recognition. Afterwards is explained the main principle of methods used for the final application. Next part is about design and implementation of this methods and conclusion is about the testing results of designed application.
Ancient Maps Digitizing
Pospíšil, Josef ; Šilhavá, Jana (referee) ; Španěl, Michal (advisor)
This work is about processing of historical maps, especially their digitizing and vectorization. The main focuses of this project are maps from the second historical military mapping and finding methods useful for removing texts from these maps.
Similarity Measure of Points of Interest in Image
Křehlík, Jan ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This document deals with experimental verifying to use machine learning algorithms AdaBoost or WaldBoost to make classifier, that is able to find point in the second picture that matches original point in the first picture. This work also depicts finding points of interest in image as a first step of finding correspondence. Next there are described some descriptors of points of interest. Corresponding points could be useful for 3D modeling of shooted scene.
Application of AdaBoost
Wrhel, Vladimír ; Šilhavá, Jana (referee) ; Hradiš, Michal (advisor)
Basics of classification and pattern recognitions will be mentioned in this work. We will focus mainly on AdaBoost algorithm, which serves to create a strong classifier function by some weak classifiers. We shall get acquainted with some modifications of AdaBoost. These modifications improve some of AdaBoost attributes. We shall also look into weak classifiers and features applicable to them. We shall especially look into the Haar- likes features. We shall discus possibilities of using the mentioned algorithms and features in facial expression recognition. We shall describe the situation between facial expression databases. We shall draw out a possible implementation of application of facial expression recognition.
Face Detection in Camera Image on a Mobile Phone
Tureček, Martin ; Láník, Aleš (referee) ; Herout, Adam (advisor)
This thesis deals with a face detection on mobile phones. It especially focuses on Windows Mobile platform. The introduction is therefore devoted to this operating system and alternatives of working with the camera. The next part of the text refers to general problems of the face detection in the image considering the weak performance of the target device. Another part of this thesis is a description of the acquisition of images from the camera using DirectShow multimedia framework and creation of a custom transformation filter for the face detection. Achieved results are summarized in the conclusion. It takes a form of tests examining different mobile devices. All difficulties arising during Windows Mobile developing are also mentioned.
Evaluation of Object Detection in Image
Černošek, Bedřich ; Behúň, Kamil (referee) ; Zemčík, Pavel (advisor)
The main goal of this bachelor's thesis was to propose the evaluation method of object detection. Result of this work was to create a program which performs the evaluation of object detection on suitable data sample and intuitively displays result to user. The task was to propose suitable experiments and dataset for proving correctness of evaluation. Part of this work was to find optimal parameters for face detection and optimal photo preprocessing before the face detection.
Recognition of Objects and Gestures in Image
Johanová, Daniela ; Beran, Vítězslav (referee) ; Zemčík, Pavel (advisor)
This thesis is focused on gesture recognition in video. The main purpose of this thesis was to create an algorithm and an application that can recognize selected gestures using a~video obtained through a~standard webcamera. The intention was to control an application program, such as video player. The approach used to achieve this goal was to exploit methods of feature extraction, tracking, and machine learning.
Object detection in images using extended set of Haar-like features and histogram-based method
Králík, Martin ; Uher, Václav (referee) ; Burget, Radim (advisor)
This diploma thesis is focused on detection in images using extended set of Haar-like features and histogram-based method. At first is introduced a basic concept of extraction and classification image features. The next part bring own concept of image features based on Diffusion distance. Result of this work is implementation this methods in Rapidminer.

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