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Feature extraction from image data
Uher, Václav ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Image processing is one area of signal analysis. This thesis is involved in feature extraction from image data and its implementation using Java programming language. The main contribution of this thesis lies in develop features extractors and their implementation in the program RapidMiner. The result is a robust tool for image analysis. The functionality of each operator is tested on mammogram images. A function model was developed for the removal of artifacts from the mammography images. The success rate of removal is comparable with other similar works. Furthermore, learning algorithms were compared on example detection of ventricle in ultrasound image.
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Implementation of wavelet transform in C++
Valouch, Lukáš ; Hasmanda, Martin (referee) ; Beneš, Radek (advisor)
The aim of this thesis is implementation of wavelet transform algorithm for noise reduction. The noise reduction itself is focused on improving informative capabilities of sonographic (ultrasound) images in medicine. For this purpose, thresholding of detailed coefficients on individual levels of multiresolution analysis was used. Common procedures were not used for searching for the most suitable thresholds of those levels. The alternative concept's design is based on fundamental empirical approach, where the individual thresholds are optimised by evolution algorithms. However, with this algorithmic procedure, more problems manifest regarding the objective evaluation of the success of noise reduction. Because of this, the program uses commonly used parameters such as mean square error of the whole image, linear slope edge approximation, relative contrast of two differently bright and distinct points and the standard deviation of compact surface. Described theoretical knowledge is used in developed application DTWT. It executes multilevel decomposition and reversed reconstruction by discrete time wavelet transform, thresholding of detailed coefficients and final evaluation of performed noise reduction. The developed tool can be used separately to reduce noise. For our purposes, it has been modified in way, that it executed through the component for evolutionary optimization of parameters (Optimize Parameters) in created scenario in RapidMiner program. In the optimization process, this component used evaluation received from DTWT program as fitness function. Optimal thresholds were sought separately for three wavelet families - Daubeschies, Symmlets and Coiflets. The evolution algorithm chose soft threshold for all three wavelet families. In comparison to hard threshold, it is more suitable for noise reduction, but it has tendencies to blur the edges more. The devised method had in most cases greater evaluated success of noise reduction with wavelet transform with threshold search done by evolution algorithms, than commonly used filters. In visual comparison however the wavelet transform introduced some minor depreciating artefacts into the image. It is always about compromise between noise reduction and maximal preservation of image information. Objectively evaluating this dilemma is not easy and is always dependant on subjective viewpoint which in case of sonographic images is that of the attending physician.
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Gestural Interface for Computer Control
Burdík, Vojtěch ; Beneš, Radek (referee) ; Přinosil, Jiří (advisor)
This work focuses on the relatively new computer branch – a computer vision. Work is concentrated on object recognition, localization and reaction to specific movements. The aim is to build a program that will be able to use hand movements to control computer, to the gesture as defined by the fingers and palms respond and make it the event. The objective should be achieved without the use of special sensors or more cameras, but only with one common webcam. For the image processing function from OpenCV library were used and program was built. Evaluation of function is based on functional verification in practice, evaluation of speed, accuracy and quality of object recognition. Following the scheme, how could program for gestural controlling the computer should look, was created, and then his realization in a simple program was made. This program is able to recognize the object in an image, in this case a hand, and through an evaluation of its movements control cursor on a computer with a possibility of simulation pressing the left mouse button. Program continuously allows the documents to scroll horizontal and vertical direction. The program is very robust and work with him is very simple.
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Image filters for evolutionary programming
Zavadil, Miloš ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Image filters is a subset of signal processing. Image filtering is mainly used for highlighting an information. It can be useful for reduce noise, smooth pictures, enhance contrast or for edge detection. Image filter design itself is a time-consuming process. It is suitable to automate the process and give up the function of filter designing to preprogrammed system. Designing komponents for that system is aim of this work. It is part of an whole expert system. A set of information is given on input which are used for generating new image filters. Subsequently it will evaluate the relevancy of concrete image filter for subsequent use.
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Application for Implementation of Digital Images Morphological Transformations
Kečkéš, Miroslav ; Beneš, Radek (referee) ; Říha, Kamil (advisor)
This thesis deals with the implementation of basic morphological operations on binary and gray-tone digital images. Partly devoted to filling in areas and thresholding, as the basic method of segmentation. The thesis is divided into two parts. The first part deals with the theoretical analysis of the various morphological operations and is divided into four chapters. The first chapter deals with basic concepts used in morphology and basic operations on binary and gray-tone images. The second chapter deals with the segmentation threshold, which is relevant for pre-treatment image. The third chapter describe the basic methods for filling areas. The last chapter deals with various functions necessary to implement the various operations in the sample application. The second part contains the actual implementation of applications.
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Linux user interface using camera
Dolníček, Petr ; Beneš, Radek (referee) ; Šmirg, Ondřej (advisor)
The goal of this was to create a fully functional program coded in C++, which is capable of real time object detection and mouse positioning in operating system Linux. Object detection is based on recognizing desired color and shape from webcam input. In this case it was a red circle. The main part of source code was generated via application Harpia. This is an application especially created for purposes of object tracking, border detection and picture processing. Most of used functions belong to OpenCV library. This library, as well as Harpia application, was created for computer vision, so it has many functions especially for purposes of my program. You can find many information about edge detection, color filtering and noise reduction in this document. I have also managed to control mouse cursor according to data that program detects. My program fulfils its purpose.
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Image data segmentation
Stodůlka, Stanislav ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Na začátku diplomové práce je čtenář seznámen s procesem zpracování obrazu a v navazující části jsou popsáný a vysvětleny dnes nejpoužívanější algoritmy pro segmentaci obrazu. Na základě watershed transform je vytvořen segmentační operátor pro volně šiřitelný program Rapid Miner a v dokumentu je popsáno, jak proces vývoje probíhal. V poslední části práce jsou prezentovány segmentované obrazy a popsána úskalí takto implementované watershed transform metody.
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Image Stabilization
Ohrádka, Marek ; Beneš, Radek (referee) ; Číka, Petr (advisor)
This thesis deals with digital image stabilization. It contains a brief overview of the problem and available methods for digital image stabilization. The aim was to design and implement image stabilization system in JAVA, which is designed for RapidMiner. Two new stabilization methods have been proposed. The first is based on the motion estimation and motion compensation using Full-search and Three-step search algorithms. The basis of the second method is the detection of object boundaries. The functionality of the proposed method was tested on video sequences with contain visible shake of the scene, which has beed created for this purpose. Testing results show that with the proper set of input parameters for the object border detection method, successful stabilization of the scene is achieved. The rate of error reduction between images is approximately about 65 to 85%. The output of the method is stabilized image sequence and a set of metadata collected during stabilization, which can be further processed in an environment of RapidMiner.
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Object Detection in Video Sequences
Šebela, Miroslav ; Beneš, Radek (referee) ; Číka, Petr (advisor)
The thesis consists of three parts. Theoretical description of digital image processing, optical character recognition and design of system for car licence plate recognition (LPR) in image or video sequence. Theoretical part describes image representation, smoothing, methods used for blob segmentation and proposed are two methods for optical character recognition (OCR). Concern of practical part is to find solution and design procedure for LPR system included OCR. The design contain image pre-processing, blob segmentation, object detection based on its properties and OCR. Proposed solution use grayscale trasformation, histogram processing, thresholding, connected component,region recognition based on its patern and properties. Implemented is also optical recognition method of licence plate where acquired values are compared with database used to manage entry of vehicles into object.
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Determination of Objects Similarity Based on Image Information
Rajnoha, Martin ; Kamencay,, Patrik (referee) ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Monitoring of public areas and their automatic real-time processing became increasingly significant due to the changing security situation in the world. However, the problem is an analysis of low-quality records, where even the state-of-the-art methods fail in some cases. This work investigates an important area of image similarity – biometric identification based on face image. The work deals primarily with the face super-resolution from a sequence of low-resolution images and it compares this approach to the single-frame methods, that are still considered as the most accurate. A new dataset was created for this purpose, which is directly designed for the multi-frame face super-resolution methods from the low-resolution input sequence, and it is of comparable size with the leading world datasets. The results were evaluated by both a survey of human perception and defined objective metrics. A hypothesis that multi-frame methods achieve better results than single-frame methods was proved by a comparison of both methods. Architectures, source code and the dataset were released. That caused a creation of the basis for future research in this field.
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