Master´s thesis deals with current problems of face detection and its parts in the infrared thermographic spectrum. Most previously published literature deals with the detection in the visible spectrum, making the thermographic detection range an interesting alternative. The work deals with the processing of image signals, images and faces in thermographic spectrum, selected methods of face detection and its parts and also deals with practical system design for detecting facial parts in this spectrum and its subsequent testing.

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.

[pt] A eletrocoagulação é um método emergente de tratamento de efluentes que combina os benefícios da coagulação, flotação e eletroquímica. Devido à complexidade inerente às operações de uma estação de tratamento de efluentes, é um desafio reagir com rapidez e precisão às condições dinâmicas necessárias para manter a qualidade do efluente. Portanto, esta tese tem como objetivo identificar a condição operacional de uma estação de tratamento de efluentes que adotou a eletrocoagulação para o tratamento de efluentes de panificação. Três condições operacionais baseadas em clarificação do efluente e lodo da reação foram as variáveis-alvo. A tese está dividida em dois ensaios. O primeiro usou sete métodos de seleção de atributos para selecionar as variáveis mais importantes em um determinado conjunto de dados. O desempenho dos modelos de classificação de redes neurais treinados no conjunto de atributos original foi comparado ao desempenho daqueles que foram treinados em um subconjunto curado usando técnicas de seleção de atributos. O modelo que utilizou a seleção de atributos apresentou o melhor desempenho (F1-score = 0,92) e uma melhoria de mais de 30 por cento na prevenção de falsos positivos. A segunda contribuição trouxe um modelo que poderia detectar o comportamento anômalo do processo usando apenas imagens coloridas da superfície do efluente obtidas através de dois módulos de câmera de tamanho pequeno. O desempenho de vários métodos, incluindo MLP, LSTM, SVM e XGBoost foi avaliado. O modelo LSTM superou os outros em termos de Precisão (84,620 por cento), Recall (84,531 por cento) e F1-score (84,499 por cento), mas o modelo XGBoost vem em segundo lugar com Precisão (83,922 por cento), Recall (82,272 por cento) e F1-score (83,005 por cento). / [en] Electrocoagulation is an emerging wastewater treatment method that combines the benefits of coagulation, flotation, and electrochemistry. As a result of the inherent complexity of processes associated with wastewater treatment plants, it is difficult to respond swiftly and correctly to the dynamic circumstances that are necessary to ensure effluent quality. Therefore, this thesis aims to identify the operational condition of a wastewater treatment plant that has adopted electrocoagulation for treating bakery wastewater. Three operational conditions based on effluent clarification and reaction sludge were the target variables. The thesis is divided into two essays. The first endeavor used seven feature selection methods to select the most important features in a given dataset. The performance of neural network classification models trained on the original feature set was compared to the performance of those that were trained on a subset of features that had been curated using feature selection techniques. The model that utilised feature selection was found to have the best performance (F1-score = 0.92) and an improvement of more than 30 percent in preventing false positives. The second contribution brought a model that could detect anomalous process behavior using only wastewater surface color images from two small-size camera modules. The performance of various methods, including MLP, LSTM, SVM, and XGBoost was assessed. The LSTM model outperformed the others in terms of macro average Precision (84.620 percent), Recall (84.531 percent), and F1-score (84.499 percent), but the XGBoost model comes closely in second with Precision (83.922 percent), Recall (82.272 percent), and F1-score (83.005 percent).

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-20T20:47:40Z No. of bitstreams: 1 ROBERTO HIGINO PEREIRA DA SILVA - DISSERTAÇÃO PPGEE 2006..pdf: 1429650 bytes, checksum: 8995a1f77f3e3471161b540826a56f6e (MD5) / Made available in DSpace on 2018-08-20T20:47:40Z (GMT). No. of bitstreams: 1 ROBERTO HIGINO PEREIRA DA SILVA - DISSERTAÇÃO PPGEE 2006..pdf: 1429650 bytes, checksum: 8995a1f77f3e3471161b540826a56f6e (MD5) Previous issue date: 2006-05-29 / A extração de objetos em uma imagem tem várias aplicações na área da automação, tais como: reconhecimento de padrões em sistemas de vigilância, visão de robôs e outros. Este trabalho apresenta um algoritmo estatístico de extração de imagens no espaço de cores RGB implementado em uma plataforma DSP e a análise dos resultados obtidos. É proposto um outro método estatístico para extração de imagens em fundo desconhecido, podendo ser homogêneo ou não- homogêneo. O algoritmo proposto tem como base o espaço de cores YCbCr , é destinado a aplicações que exigem performance e tolerância a um determinado intervalo de erro. Utiliza a métrica dos máximos para determinar a distância entre os vetores desse espaço, sendo capaz de suportar pequenas variações de luminosidade. Apresenta- se a simulação que validou a funcionalidade desse algoritmo. / The images objects embedded extraction has several applicationns in theautomation area, such as: patterns recognition in surveillance systems, robots vision and others. An image statistical extraction algorithm in the RGB colors space was implemented in a DSP`plataform and the obtained results analysis are presented in this dissertation. We propose a new statistical method for objects extraction in an unknown background (non-homogenous or homogenous), using the YCbCr space. It uses maximum metric to determine its distances betwenn the space vectors, being capable to suport small global variations and places of brightness. They are presented the simulation results that validate the algorithm functionality for applications that demand performance and be tolerant to a determined error interval.

The thesis deals with colors - their representation in digital devices and how to provide the best color preservation accross different devices. In the first part of the work, the knowledge of colors and human vision is briefly summarized. Then color models and color spaces are elaborated, mainly those device independent. Spectrum of colors viewable or printable on a device - the gamut - is different for every device and there's a need of precise reproduction or record of color. That's why the system of color management is described further and especially the gamut mapping approaches and algorithms are mentioned. In the second part of the work, the implementation of how two algorithms of color gamut mapping (HPMINDE, SCLIP) can be implemented in MATLAB is described. In the third and last part of the work, the results of implemented algorithms are presented and discussed. These results are compared to results of commonly used color gamut mapping technique (Adobe Photoshop).

With the rapidly growing computational power of modern computers, physically based rendering has found its way into real world applications. Real-time simulations and renderings of fire and smoke had become one major research interest in modern video game industry, and will continue being one important research direction in computer graphics. To visually recreate realistic dynamic fire and smoke is a complicated problem. Furthermore, to solve the problem requires knowledge from various areas, ranged from computer graphics and image processing to computational physics and chemistry. Even though most of the areas are well-studied separately, when combined, new challenges will emerge. This thesis focuses on three aspects of the problem, dynamic, real-time and realism, to propose a solution in form of a GPGPU pipeline, along with its implementation. Three main areas with application in the problem are discussed in detail: fluid simulation, volumetric radiance estimation and volumetric rendering. The weights are laid upon the first two areas. The results are evaluated around the three aspects, with graphical demonstrations and performance measurements. Uniform grids are used with Finite Difference (FD) discretization scheme to simplify the computation. FD schemes are easy to implement in parallel, especially with ComputeShader, which is well supported in Unity engine. The whole implementation can easily be integrated into any real-world applications in Unity or other game engines that support DirectX 11 or higher.