This thesis covers design and practical realization of a tool for quick search in large image databases, containing from tens to hundreds of thousands photos, based on image similarity. The proposed technique uses various methods of descriptor extraction, creation of Bag of Words dictionaries and methods of storing image data in PostgreSQL database. Further, experiments with the implemented software were carried out to evaluate the search time effectivity and scaling possibilities of the design solution.

Thesis in theoretical part deals with the procedures used in image databases searching. There are discussed two basic possible approaches - text based searching and content based searching. In next section there are described methods for image similarity detection. Practical part deals with detailed description and implementation of three selected image features used for image searching. In third part there are presented testing procedure for implemented algorithms and test results. In conclusion implementation of Rapidminer operator are described. This operator uses all implemented algorithms and allows image similarity matching, searching for most similar images in database, and copy these images to output folder.

The proposition of company KERAMIS koupelny s.r.o. strategic business activities are the graduation thesis topic. I worked individual strategic analyses (PEST analysis, 5 powers Porter's model, value deskriptor analysis, financial analysis and SWOT analysis) and I designated concrete stability strategy on the basis of analyses results in relation to marketing, R&D, human resources, finance and products. According to my investigations the firm should continue in its business branch and shouldn't broaden its business in whole building industries. The firm hat to decrease its indebtedness, search all the time new product suppliers, who offer better trading conditions and new products, endeavour to canvass exclusive dealership in the region and financially motivate staffs depending on their staff productivity. Further I advise 3D graphics computer software and delivery van buying and investment in websites optimalization (SEO). The future firm progression depends on financial resources sufficiency and subsequent occasions realization.

In this thesis deep convolutional neural networks models and feature descriptor models are compared. Feature descriptors are paired with suitable chosen classifier. These models are a part of machine learning therefore machine learning types are described in this thesis. Further these chosen models are described, and their basics and problems are explained. Hardware and software used for tests is listed and then test results and results summary is listed. Then comparison based on the validation accuracy and training time of these said models is done.

Microstructure characterization and reconstruction (MCR) is an important prerequisite for empowering and accelerating integrated computational materials engineering. Much progress has been made in MCR recently; however, in the absence of a flexible software platform it is difficult to use ideas from other researchers and to develop them further. To address this issue, this work presents MCRpy as an easy-to-use, extensible and flexible open-source MCR software platform. MCRpy can be used as a program with graphical user interface, as a command line tool and as a Python library. The central idea is that microstructure reconstruction is formulated as a modular and extensible optimization problem. In this way, arbitrary descriptors can be used for characterization and arbitrary loss functions combining arbitrary descriptors can be minimized using arbitrary optimizers for reconstructing random heterogeneous media. With stochastic optimizers, this leads to variations of the well-known Yeong–Torquato algorithm. Furthermore, MCRpy features automatic differentiation, enabling the utilization of gradient-based optimizers. In this work, after a brief introduction to the underlying concepts, the capabilities of MCRpy are demonstrated by exemplarily applying it to typical MCR tasks. Finally, it is shown how to extend MCRpy by defining a new microstructure descriptor and readily using it for reconstruction without additional implementation effort.

This thesis deals with description of existing methods of image retrieval. It contains set of methods for image description, coding of global and local descriptor (SIFT, etc.) and describes method of effective searching in multidimensional space (LSH). It continues with proposal and testing of three global descriptors using color histograms, histogram of gradients and the combination of both. The last part deals with similar image retrieval using proposed descriptors and the indexing method LSH and compares the results with the existing method. Product of this work is an experimental application which demonstrates the proposed solution.

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.

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5.4pt;mso-para-margin:0in;mso-para-margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:11.0pt;font-family:"Calibri","sans-serif";mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:"Times New Roman";mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}</style><![endif]--><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">The </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">t</span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">hesis investigates development, improvement and evaluation of methods for quantitative characterization of objects from their digital images and similarity measurements between digital images. Methods for quantitative characterization of objects from their digital images are increasingly used in applications in which error can </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">have crtical consequences, </span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">but the traditional methods for shape quantification are of low precision and accuracy. </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">In the thesis is shown </span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">that the </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">coverage of a pixel by a shape can</span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA"> be used to highly improve the accuracy and precision of using digital images to estimate the maximal distance between objects </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">furthest points measured in a given direction. It is highly desirable that a distance measure between digital images can be related to a certain shape property and morphological operations are used when defining a distance for this purpose. Still, the distances defined in this manner turns out to be insufficiently sensitive to relevant data representing shape properties in images. We show that the idea of adaptive mathematical morphology can be used successfully to overcome problems related to sensitivity of distances defined via morphological operations when comparing objects from their digital image representations.</span></p> / <p>У тези су размотрени развој, побољшање и евалуација метода за квантитативну карактеризацију објеката приказаних дигиталним сликама, као и мере растојања између дигиталних слика. Методе за квантитативну карактеризацију објеката представљених дигиталним сликама се&nbsp; све више користе у применама у којима грешка може имати критичне последице, а традиционалне методе за&nbsp; квантитативну карактеризацију су мале прецизности и тачности. У тези се показује да се коришћењем информације о покривеност пиксела обликом може значајно побољшати прецизност и тачност оцене растојања између две најудаљеније тачке облика мерено у датом правцу. Веома је пожељно да мера растојања између дигиталних слика може да се веже за одређену особину облика и морфолошке операције се користе приликом дефинисања растојања у ту сврху. Ипак, растојања дефинисана на овај начин показују се недовољно осетљива на релевантне податке дигиталних слика који представљају особине облика. У тези се показује да идеја адаптивне математичке морфологије може успешно да се користи да би се превазишао поменути&nbsp; проблем осетљивости растојања дефинисаних користећи морфолошке операције.</p> / <p>U tezi su razmotreni razvoj, poboljšanje i evaluacija metoda za kvantitativnu karakterizaciju objekata prikazanih digitalnim slikama, kao i mere rastojanja između digitalnih slika. Metode za kvantitativnu karakterizaciju objekata predstavljenih digitalnim slikama se&nbsp; sve više koriste u primenama u kojima greška može imati kritične posledice, a tradicionalne metode za&nbsp; kvantitativnu karakterizaciju su male preciznosti i tačnosti. U tezi se pokazuje da se korišćenjem informacije o pokrivenost piksela oblikom može značajno poboljšati preciznost i tačnost ocene rastojanja između dve najudaljenije tačke oblika mereno u datom pravcu. Veoma je poželjno da mera rastojanja između digitalnih slika može da se veže za određenu osobinu oblika i morfološke operacije se koriste prilikom definisanja rastojanja u tu svrhu. Ipak, rastojanja definisana na ovaj način pokazuju se nedovoljno osetljiva na relevantne podatke digitalnih slika koji predstavljaju osobine oblika. U tezi se pokazuje da ideja adaptivne matematičke morfologije može uspešno da se koristi da bi se prevazišao pomenuti&nbsp; problem osetljivosti rastojanja definisanih koristeći morfološke operacije.</p>

This master thesis deals with usage of machine learning methods in computer vision for classification of unknown images. The first part contains research of available machine learning methods, their limitations and also their suitability for this task. The second part describes the processes of creating training and testing gallery. In the practical part, the solution for the problem is proposed and later realised and implemented. Proper testing and evaluation of resulting system is conducted.

This diploma thesis deals with the problem of mobile robot localisation in the environment based on current 2D and 3D sensor data and previous records. Work is focused on detecting previously visited places by robot. The implemented system is suitable for loop detection, using the Gestalt 3D descriptors. The output of the system provides corresponding positions on which the robot was already located. The functionality of the system has been tested and evaluated on LiDAR data.