Longtime Video

Tato práce pojednává o postupech používaných při tvorbě časosběrného videa ze sady fotografií a nástrojích, které ji usnadňují. Navrhuje a hodnotí různé přístupy použitelné při vyřazování odlišných snímků ze sekvence, aplikaci digitálních obrazových filtrů a další využitelné funkce. Praktickou částí práce je aplikace, která tyto metody a funkce implementuje.This thesis describes methods used for making time-lapse video from a set of photographs and tools, which make it easier. It suggests and evaluates different approaches useful for elimination of frames, which differ from the rest of the set, application of digital image filters and other useful features. Practical part of this work is a computer program implementing these methods and features.

DETECTION OF GRANULATION TISSUE FOR HEALING ASSESSMENT OF CHRONIC ULCERS

Wounds that fail to heal within an expected period develop into ulcers that cause severe pain and expose patients to limb amputation. Ulcer appearance changes gradually as ulcer tissues evolve throughout the healing process. Dermatologists assess the progression of ulcer healing based on visual inspection of ulcer tissues, which is inconsistent and subjective. The ability to measure objectively early stages of ulcer healing is important to improve clinical decisions and enhance the effectiveness of the treatment. Ulcer healing is indicated by the growth of granulation tissue that contains pigment haemoglobin that causes the red colour of the tissue. An approach based on utilising haemoglobin content as an image marker to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers is investigated in this study. The approach is utilised to develop a system that is able to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers

Automatic Selection of Representative Pictures

Na internetu jsou miliardy fotografií a s neustále rostoucí velikostí těchto digitálních úložišť je stále více složitější vyhledat určitou snímku. Na zvýšení informační kvality fotoalb navrhujeme novou metodu, která vybírá reprezentativní snímky ze skupiny fotografií s využitím algoritmů počítačového vidění. Cílem této práce je analýza problematiky význačných znaků obrázků, porovnávání obrázků, shlukování objektů a také má za úkol prozkoumat charakteristické vlastnosti fotografií. Testy ukazují, že neexistuje univerzální příznak popisující fotografie takovým způsobem, aby bylo možné jednoduše modelovat proces shlukování vykonávaný lidským viděním. Práce navrhuje hybridní algoritmus, který kombinuje použití výhodných vlastností vybraných příznaků fotografie spolu s využitím specializovaného vícekrokového shlukovacího algoritmu. Klíčovou myšlenkou postupu je, že častěji fotografované objekty jsou pravděpodobněji reprezentativní. Tedy platí, že již náhodným výběrem z největších shluků dostáváme určitým způsobem reprezentativní fotografie. Tento výběr je dále vylepšený na základe optimalizací, které upřednostňují snímky s lepšími fotografickými vlastnostmi.There are billions of photos on the internet and as the size of these digital repositories grows, finding target picture becomes more and more difficult. To increase the informational quality of photo albums we propose a new method that selects representative pictures from a group of photographs using computer vision algorithms. The aim of this study is to analyze the issues about image features, image similarity, object clustering and examine the specific characteristics of photographs. Tests show that there is no universal image descriptor that can easily simulate the process of clustering performed by human vision. The thesis proposes a hybrid algorithm that combines the advantages of selected features together using a specialized multiple-step clustering algorithm. The key idea of the process is that the frequently photographed objects are more likely to be representative. Thus, with a random selection from the largest photo clusters certain representative photos are obtained. This selection is further enhanced on the basis of optimization, where photos with better photographic properties are being preferred.

Evaluation of focus curves based on goodness criteria

In smartphones there are restrictions for imaging systems like computation capabilities, power and physical size, which have caused usage of relatively low quality camera sensors and modules. To achieve acceptable image quality, low quality images are enhanced and processed with many different algorithms. These algorithms can be executed in different order in the imaging pipeline. Poor order may cause processing blocks executed later to create something undesired to images while in optimal order each processing block should enhance image quality. One very important block is autofocus (AF) statistics calculation block. Poor AF statistics may cause AF algorithm to choose incorrect focus point, which may cause image to become blurred. In addition of producing low quality images, blurry images may cause big problems for later processing blocks in imaging pipeline. This thesis is done for Intel Finland Oy. The thesis is about studying how much different execution orders of processing blocks affect to accuracy of AF algorithm. To study the subject images were captured from same scene with different focus lens positions and evaluated how easily some AF algorithm could find the best focus point. For that task single statistic was calculated for each differently focused image, which allowed plotting of focus curve. As statistic average amount of edge content in image was used. To calculate it images were filtered with high pass filter. This kind of filtering discards low frequency information and takes to account higher frequency content, which contains mostly information of edges. For evaluating focus curves goodness criteria were developed. Goodness criteria represent the capability of recognizing spike, where image is correctly focused, from focus curve. In this study it was noticed that decreasing noise made task of AF algorithm significantly easier. Also reasonable downscaling improved situation for AF algorithm, but it also caused time to time something unexpected behavior. On the other hand color correction is something that should be done after AF statistics calculation, because it emphasizes noise

Computer Vision Aided Print Pattern Generation in Inkjet Printed Electronics

Inkjet printed electronics is one of the new promising electronics manufacturing techniques out there. It has become a widely adopted manufacturing method especially in the field of low-cost electronics. This thesis considers an application of inkjet printed electronics where conductive ink is used for printing the connections between the components on a single unit called a module. The base module is fabricated by molding the components together such that the connection points of the components form a level surface. After this, the wiring is printed on top. Because of the inaccuracies in the fabrication process, there is often a mismatch between the designed print pattern and the target module. The purpose of this thesis is to introduce an online print pattern generation system that uses computer vision to detect the locations of the module components and then modifies the print pattern accordingly. By integrating the print pattern generation system as a part of the manufacturing process, not only is it possible to print functioning modules but also multiple modules can be printed at the same time. This way the capabilities of inkjet printed electronics can be more efficiently harnessed. The experiments prove that the developed print pattern correction system together with the proposed imaging setup are able to produce desired results in practice. In addition to successfully printing ten modules at once, it is also shown that the developed system is robust and generalizes well for different types of modules. /Kir1

DETECTION OF GRANULATION TISSUE FOR HEALING ASSESSMENT OF CHRONIC ULCERS

Wounds that fail to heal within an expected period develop into ulcers that cause severe pain and expose patients to limb amputation. Ulcer appearance changes gradually as ulcer tissues evolve throughout the healing process. Dermatologists assess the progression of ulcer healing based on visual inspection of ulcer tissues, which is inconsistent and subjective. The ability to measure objectively early stages of ulcer healing is important to improve clinical decisions and enhance the effectiveness of the treatment. Ulcer healing is indicated by the growth of granulation tissue that contains pigment haemoglobin that causes the red colour of the tissue. An approach based on utilising haemoglobin content as an image marker to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers is investigated in this study. The approach is utilised to develop a system that is able to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers

Compressão de imagem e vídeo com controlador ARM

Este trabalho foi desenvolvido num estágio na empresa ABS GmbH sucursal em Portugal, e teve como foco a compressão de imagem e vídeo com os padrões JPEG e H.264, respetivamente. Foi utilizada a plataforma LeopardBoard DM368, com um controlador ARM9. A análise do desempenho de compressão de ambos os padrões foi realizada através de programas em linguagem C, para execução no processador DM368. O programa para compressão de imagem recebe como parâmetros de entrada o nome e a resolução da imagem a comprimir, e comprime-a com 10 níveis de quantização diferentes. Os resultados mostram que é possível obter uma velocidade de compressão até 73 fps (frames per second) para a resolução 1280x720, e que imagens de boa qualidade podem ser obtidas com rácios de compressão até cerca de 22:1. No programa para compressão de vídeo, o codificador está configurado de acordo com as recomendações para as seguintes aplicações: videoconferência, videovigilância, armazenamento e broadcasting/streaming. As configurações em cada processo de codificação, o nome do ficheiro, o número de frames e a resolução do mesmo representam os parâmetros de entrada. Para a resolução 1280x720, foram obtidas velocidades de compressão até cerca de 68 fps, enquanto para a resolução 1920x1088 esse valor foi cerca de 30 fps. Foi ainda desenvolvida uma aplicação com capacidades para capturar imagens ou vídeos, aplicar processamento de imagem, compressão, armazenamento e transmissão para uma saída DVI (Digital Visual Interface). O processamento de imagem em software permite melhorar dinamicamente as imagens, e a taxa média de captura, compressão e armazenamento é cerca de 5 fps para a resolução 1280x720, adequando-se à captura de imagens individuais. Sem processamento em software, a taxa sobe para cerca de 23 fps para a resolução 1280x720, sendo cerca de 28 fps para a resolução 1280x1088, o que é favorável à captura de vídeo