Este trabalho apresenta uma metodologia para inspeção de lentes oftalmológicas orgânicas esféricas durante seu processo de polimento. A metodologia consiste na obtenção de uma imagem em uma câmera de vídeo CCD, usando-se luz ultravioleta, da lente a ser inspecionada, e posterior processamento desta imagem para discriminar a presença de riscos de outros artefatos que poderão aparecer na imagem capturada. Para a detecção da presença de riscos foram utilizados os descritores de Fourier. Atenção especial foi dada à iluminação da lente, que é fator determinante na obtenção de uma boa qualidade de imagem. Os resultados mostram a eficiência do método e permitem sua utilização durante o processo de fabricação de lentes. / This work presents a methodology for inspection of spherical organic ophthalmic lenses during the polishing process. The methodology encompasses the capture of an ultraviolet image of the lens under inspection by a CCD video camera and associated processing of the image to discriminate between scratches on the lens and artifacts that can appear on the image. Fourier descriptors were used to detect the existence of scratches. Special attention was given to illumination which is a determining factor in grabbing an image with good quality. The results show that the method is efficient and that it can be used in the lens manufacturing process.

Este trabalho apresenta uma metodologia para inspeção de lentes oftalmológicas orgânicas esféricas durante seu processo de polimento. A metodologia consiste na obtenção de uma imagem em uma câmera de vídeo CCD, usando-se luz ultravioleta, da lente a ser inspecionada, e posterior processamento desta imagem para discriminar a presença de riscos de outros artefatos que poderão aparecer na imagem capturada. Para a detecção da presença de riscos foram utilizados os descritores de Fourier. Atenção especial foi dada à iluminação da lente, que é fator determinante na obtenção de uma boa qualidade de imagem. Os resultados mostram a eficiência do método e permitem sua utilização durante o processo de fabricação de lentes. / This work presents a methodology for inspection of spherical organic ophthalmic lenses during the polishing process. The methodology encompasses the capture of an ultraviolet image of the lens under inspection by a CCD video camera and associated processing of the image to discriminate between scratches on the lens and artifacts that can appear on the image. Fourier descriptors were used to detect the existence of scratches. Special attention was given to illumination which is a determining factor in grabbing an image with good quality. The results show that the method is efficient and that it can be used in the lens manufacturing process.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-06-03T23:48:41Z No. of bitstreams: 1 EdsonJacksonDeMedeirosNeto_DISSERT.pdf: 2349422 bytes, checksum: 58dbff032ce7a77c69ab57cce418be2d (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-06-07T19:55:39Z (GMT) No. of bitstreams: 1 EdsonJacksonDeMedeirosNeto_DISSERT.pdf: 2349422 bytes, checksum: 58dbff032ce7a77c69ab57cce418be2d (MD5) / Made available in DSpace on 2016-06-07T19:55:39Z (GMT). No. of bitstreams: 1 EdsonJacksonDeMedeirosNeto_DISSERT.pdf: 2349422 bytes, checksum: 58dbff032ce7a77c69ab57cce418be2d (MD5) Previous issue date: 2015-11-09 / O grande volume de dados gerados como resultado da supervis?o de processos de automa??o na ind?stria gerou como consequ?ncia um vasto espa?o de armazenamento em disco, assim como dificuldade na transmiss?o destes dados por links de telecomunica??es. Os algoritmos de compress?o com perda de dados surgiram na d?cada de 90 com intuito de solucionar estes problemas, passando a serem utilizados em sistemas de supervis?o industrial para a compress?o de dados em tempo real. Para isso estes foram projetados para eliminar informa??es redundantes e indesejadas de forma simples e eficiente. No entanto, os par?metros destes algoritmos necessitam de serem configurados para cada vari?vel de processo, tornando invi?vel a configura??o manual em caso de sistemas que supervisionam milhares de vari?veis. Nesse contexto este trabalho prop?e o algoritmo Adaptive Swinging Door Trending, que consiste numa adapta??o do Swinging Door Trending, em que seus principais par?metros s?o ajustados dinamicamente atrav?s da an?lise de tend?ncias do sinal. Prop?e-se tamb?m uma an?lise comparativa de desempenho dos algoritmos de compress?o com perda de dados aplicados sobre vari?veis de processo de s?ries temporais e cartas dinamom?tricas de fundo de po?o. Os algoritmos abordados para efeito comparativos foram os lineares por partes e os de transformadas. / The great amount of data generated as the result of the automation and process supervision in industry implies in two problems: a big demand of storage in discs and the difficulty in streaming this data through a telecommunications link. The lossy data compression algorithms were born in the 90?s with the goal of solving these problems and, by consequence, industries started to use those algorithms in industrial supervision systems to compress data in real time. These algorithms were projected to eliminate redundant and undesired information in a efficient and simple way. However, those algorithms parameters must be set for each process variable, becoming impracticable to configure this parameters for each variable in case of systems that monitor thousands of them. In that context, this paper propose the algorithm Adaptive Swinging Door Trending that consists in a adaptation of the Swinging Door Trending, as this main parameters are adjusted dynamically by the analysis of the signal tendencies in real time. It?s also proposed a comparative analysis of performance in lossy data compression algorithms applied on time series process variables and dynamometer cards. The algorithms used to compare were the piecewise linear and the transforms.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-07-22T15:28:33Z No. of bitstreams: 1 RamonAugustoSousaLins_DISSERT.pdf: 3798892 bytes, checksum: 0a5d06ff47c763499839e741148b3dcb (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-07-27T22:14:28Z (GMT) No. of bitstreams: 1 RamonAugustoSousaLins_DISSERT.pdf: 3798892 bytes, checksum: 0a5d06ff47c763499839e741148b3dcb (MD5) / Made available in DSpace on 2016-07-27T22:14:28Z (GMT). No. of bitstreams: 1 RamonAugustoSousaLins_DISSERT.pdf: 3798892 bytes, checksum: 0a5d06ff47c763499839e741148b3dcb (MD5) Previous issue date: 2015-12-04 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / Neste trabalho ? proposto o desenvolvimento de um sistema inteligente capaz de segmentar, contar e classificar individualmente dentes a partir de imagens fotogr?ficas digitais intraorais oclusais.O sistema proposto faz uso combinado das t?cnicas de aprendizagem de m?quina no caso a m?quina de vetor de suporte e processamento digital de imagens. Primeiramente ? feita uma segmenta??o baseada nas cores dos dentes e n?o dentes presentes na imagem atrav?s do uso de m?quina de vetores de suporte. A partir da identifica??o das regi?es de interesse, dentes e n?o dentes, os dados s?o representados de modo que a contagem, detec??o de fronteiras e classifica??o dos dentes possa ser feita. Para contagem e detec??o de fronteiras s?o utilizadas t?cnicas baseadas em operadores morfol?gicos, eros?o e transformada watershed, respectivamente. A classifica??o quanto aos tipos de dentes ? baseada na utiliza??o dos descritores de posi??o e forma, sendo esse ?ltimo definido por descritores de Fourier. O sistema portanto ? capaz de realizar a segmenta??o, a contagem e a classifica??o de dentes presentes nas imagens. / Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it?s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Made available in DSpace on 2014-12-17T14:55:21Z (GMT). No. of bitstreams: 1 FabioSL_TESE.pdf: 5888891 bytes, checksum: cd954df5e4af671c3361060293cc5710 (MD5) Previous issue date: 2014-05-30 / Universidade Federal do Rio Grande do Norte / The precision and the fast identification of abnormalities of bottom hole are essential to prevent damage and increase production in the oil industry. This work presents a study about a new automatic approach to the detection and the classification of operation mode in the Sucker-rod Pumping through dynamometric cards of bottom hole. The main idea is the recognition of the well production status through the image processing of the bottom s hole dynamometric card (Boundary Descriptors) and statistics and similarity mathematics tools, like Fourier Descriptor, Principal Components Analysis (PCA) and Euclidean Distance. In order to validate the proposal, the Sucker-Rod Pumping system real data are used / A identifica??o r?pida e precisa de anormalidades de fundo de po?o ? essencial para evitar danos e aumentar a produ??o na ind?stria do petr?leo. Esta tese apresenta um estudo sobre uma nova abordagem autom?tica para a detec??o e classifica??o de modos de opera??o no sistema de Bombeio Mec?nico atrav?s de carta de dinamom?tricas de fundo de po?o. A id?ia principal ? o reconhecimento das condi??es de produ??o do sistema atrav?s do processamento de imagem do carta dinamom?trica de fundo de po?o (Descritores de Fourier) e ferramentas matem?ticas estat?sticas (An?lise de Componentes Principais - PCA) e de similaridade (Dist?ncia Euclidiana). Para validar a proposta, s?o utilizados dados provenientes de sistemas de Bombeio Mec?nico reais