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On-line gap measurement techniques for steel mill non-contacting conveyance system, which can supply accurate, rapid and high-sampling rate gap measurements, have been proposed. To realize the entire process, by considering the operational environment in a steel mill and combining with those available system dimension measurement instruments, an image-based scheme with proper image processing and parameter calibration process has been developed. The possible sources that affect the air-gap detection accuracies have also been thoroughly investigated, and a comprehensive measurement database and a recursive modification technique have been successfully established. In order to achieve stable control for site implementation, an integrated optical inspection system which combined with the high-speed rate line-scan camera has been designed. From the experimental results, the proposed system can both provide accurate gap values at the static state, and offer stable control operations at the dynamic state. It is believed that the proposed scheme provide innovated guidance for the related conveyance applications in the steel mill.

Natural fibres are increasingly being considered as the reinforcement for polymer matrix composites as they are perceived to be sustainable being a renewable resource. However, they suffer from higher variability in mechanical properties and concerns about their long-term durability in a moist environment. In this study the physical properties of the jute fibres were characterised, the fibre length distribution was determined and the fibre cross-section was analysed using digital images. It was observed that the true fibre area followed a log-normal distribution. The fibre area distribution for different geometrical shapes was estimated and the error in the estimated area of assumed fibre cross-section was also determined to assess the applicability of the assumed cross-section. The mechanical properties of the jute technical fibres from a single batch from South Asia were determined; fibre tensile tests were carried out at ten different gauge lengths between 6 mm and 300 mm and the Young’s modulus, strain to failure and ultimate tensile strengths were determined individually. A strong correlation was observed between the fibre strength/fracture strain and fibre gauge length. It was found as the gauge length increases the fibre strength/fracture strain drops. The fibre failure (Strength/Strain) was modelled using Weibull distribution and three statistical models were developed to relate the fibre strength/fracture strain to the fibre gauge length. Examination of tensile test data reveals that the coefficient of variation (CoV) for failure strain is consistently lower than the CoV for fracture stress (strength), as the failure strain is weakly influenced by the fibre cross-section. Hence, failure strain is the more consistent failure criterion and it is recommended to use failure strain as the key design criterion for natural fibre composites in order to improve reliability in the design of these materials. Different authors have tried to model natural fibre reinforced polymer elastic modulus using micromechanical models and have suggested that further study should include fibre angle and length distribution factors to improve the micromechanical prediction. This thesis further seeks to validate a novel methodology for the prediction of the tensile modulus and strength of natural fibre composites through careful consideration of each of the parameters in the rule of mixtures along with consideration of the statistical variation inherent in reinforcements extracted from plants. The tensile modulus and strength of jute fibre reinforced composites manufactured from well characterised fibres was measured experimentally. Six well established micromechanical models were used to predict the composite elastic modulus. Two micromechanical models were used to predict composite strength. For both mechanical properties, the inclusion of a fibre area correction factor to account for the non-circular cross-section of the fibre resulted in an improved prediction of the respective mechanical properties.

"Non-destructive testing (NDT) is critical to many precision industries because it can provide important information about the structural health of critical components and systems. In addition, NDT can also identify situations that could potentially lead to critical failures. Specifically, NDT by optical methods have become popular because of their non-contact and non-invasive nature. Shearography is a high-resolution optical NDT method for identification and characterization of structural defects in components and has gained wide acceptance over the last decade. Traditional workflow of NDT by shearography has been determined to be inefficient, due to the requirements of having experienced operators that must determine the most suitable loading methods to identify defects in samples under testing as well as to determine the best system arrangement for obtaining the maximum measuring sensitivity. To reduce the number of experiments that are required and to allow inspectors to perform NDT by laser shearography in a more efficient way, it is necessary to optimize the experimental workflow. The goal of the optimization would be an appropriate selection of all experimental variables including loading methods, boundary conditions, and system¡¯s sensitivities, in order to avoid repeating experiments several times in the processes of components characterization and health monitoring. To achieve this goal, a hybrid approach using shearographic fringe prediction with Finite Element Analysis (FEA) has been developed. In the FEA simulations, different loading conditions are applied to samples with defects, and in turn, the shearographic fringes are predicted. Fringe patterns corresponding to specific loading conditions that are capable of detecting defects are chosen and experimental tests are performed using those loading conditions. As a result, using this approach, inspectors could try different combinations of loading methods, and system¡¯s sensitivities to investigate and select appropriate experimental parameters to improve defect detection capabilities of the system by using low-cost computer simulations instead of lengthy and expensive experiments. In addition, to improve the identification of defects on the sample, camera calibration and image registration algorithms are used to project the detected defects on the sample itself to locate and visualize the position of defects during shearographic investigations. This hybrid approach is illustrated by performing NDT of a plate made of acrylic that has a partial hole at the center. Fringe prediction with finite element analysis are used to characterize the optimized experimental procedures and in turn, corresponding measurements are performed. A multimedia projector is employed to project the defects on the surface of the plate in order to visualize the location of the partial hole (defect). Furthermore, shearographic system is used for other applications including NDT of a composites plate and of a thin latex membrane. The procedures shows the effectiveness of the approach to perform NDT with shearography methods. "

In the study of computer vision, background modeling is a fundamental and critical task in many conventional applications. This thesis presents an introduction to background modeling and various computer vision techniques for estimating the background model to achieve the goal of removing dynamic objects in a video sequence. The process of estimating the background model with temporal changes in the absence of foreground moving objects is called adaptive background modeling. In this thesis, three adaptive background modeling approaches were presented for the purpose of developing \teacher removal" algorithms. First, an adaptive background modeling algorithm based on linear adaptive prediction is presented. Second, an adaptive background modeling algorithm based on statistical dispersion is presented. Third, a novel adaptive background modeling algorithm based on low rank and sparsity constraints is presented. The design and implementation of these algorithms are discussed in detail, and the experimental results produced by each algorithm are presented. Lastly, the results of this research are generalized and potential future research is discussed.

This study proposes a novel microfluidic system based on a computer controlled digital image processing (DIP) technique and optical tweezers for automatic cell/microparticle recognition, counting and sorting in a continuous flow environment. In the proposed system, the cells/microparticles are focused electrokinetically into a narrow sample stream and are then driven through the region of interest (ROI), where they are recognized and traced in real time using a proprietary DIP system. Synchronized control signals generated by the DIP system are then used to actuate a focused IR laser beam to displace the target cells from the main sample stream into a neighboring sheath flow, which carries them to a downstream collection channel where they are automatically counted. The proposed approach makes possible the continuous sorting and counting of cell samples without the need for any moving parts or embedded transducers. The experimental results show that the proposed system is capable of sorting 5 £gm or 10 £gm PS bead from a mixture of 5 £gm and 10 £gm samples in the flow speed 300 £gm/sec. The proposed system provides a simple, low-cost, high-performance solution for cell manipulation in microfluidic devices.

In this study, visibility observation, aerosol sampling, statistical analysis and model regression were conducted to investigate the influence of suspended particle characteristics and pollution sources on visibility and extinction coefficient in Koahsiung metropolitan area. The scene monitored by a digital camera was then proceeded by digital image processing and were then compared with observed atmospheric visibility observation. Meteorological parameters of various weather patterns (including relative humidity, wind direction, wind speed and mixing height ) played important roles on the reduction of visibility in metropolitan area. Synoptic charts were collected over the 1992-1999 period to analyze their influence on ambient air quality. This study revealed that high PM10 concentration and unhealthful PSI index occurred at weather patterns of high pressure outflow style I and circus-sluice of high pressure outflow¡C Regular visibility was observed during the period of November 1998- April 2000. The highest visibility was above 20 km while the lowest visibility was loss than 1 km in Koahsiung metropolitan area. The observed visibility was mainly distribution over the 2-6 km. The visibility below 6 km were about 61.88% of total observation days and poor visibility was usually occurred in winter. Besides, intensive visibility observation was conducted in January and March, 2000. Visibility was observed hourly at Kaohsiung Meteorological Station and Fa-Shin Temple, respectively. Suspended particles were continuously sampled for five hours at Chien-Chen, Sen-Min and Chien-Gin ambient air quality stations. These measurements were conducted to investigate the influence of chemical and physical properties of suspended particle and meteorological parameters on visibility and extinction coefficient in Koahsiung metropolitan area. Receptor model was applied to understand the emission sources of fine particles (PM2.5) and investigate the influence of emission sources on visual air quality. In addition, the determination of visibility by imagine processing was discussed. Visibility observation was coincided with scene monitoring in order to clarify the relationship between image processing and observed visibility. A illumination eigenvalue calculated by picture transfer software was used to correlate with observed visibility. This study revealed that, illumination eigenvalue and observed visibility had strong negative correlation (R=-0.9079) at effective visual range of 5-10 km. Results form single-factor analysis indicated that no significant variation of aerosol particle concentration was observed at three ambient air quality stations. A bi-mode size distribution of aerosol particles was observed for most stations in Koahsiung metropolitan area. The peak aerodynamic diameter of fine and coarse particles was observed at 0.56-1.0

The area of the digital image processing is getting more attention in the hope that it will increase the accuracy of any scientific measurements, such as in determining an object velocity, temperature, and size. While human vision is excellent to recognize and differentiate objects, it has been proven to be a poor tool when it comes to measure the object performance. One of many digital image processing applications is texture analysis whose purpose is to evaluate image patterns. The purpose of this dissertation is to investigate the use of texture analysis as a tool to micro fiber dispersion measurement. Micro fiber dispersion can be found in many applications such as in paper and industry powder engineering. Three cases related to micro fiber dispersion were investigated in this study. The first case was the experimental study of the dispersion in open water channel. Sets of synthetic fibers were put into water channel to simulate a process that can be found in papermaking industry. The research investigated the effect of three operating parameters: fluid velocity, fiber consistency, and fiber aspect ratio to fiber dispersion. Using two-factorial experimental design technique, the main and interaction effects of these parameters were evaluated. The study found that increasing fluid velocity, fiber aspect ratio, and consistency decreased the dispersion level. The study also found that the effect of individual parameters is more pronounced than the role of the interactive terms on the fiber flocculation. The second case considered was applying the fiber dispersion analysis to computer-synthesized images consisting of different arrangements of fibers. Four sets of sub-cases were presented. These sub-cases were divided based on the fiber-concentrated location and fiber distribution. The use of computer-synthesized images was found to be very useful to simulate real situation during fiber dispersion. The third case investigated the fiber distribution on a dry paper. Images for different types of paper were taken and evaluated to see the dispersion level of each type of paper. It was found that the current texture analysis was applicable to determine the dispersion level for dry papers. While three cases indicated that the texture analysis can be used to investigate the fiber dispersion, the texture analysis used here is not a perfect and universal method and may not be suitable to analyze other types of dispersions. The human vision will always be essential to determine if the texture analysis is applicable to any other problem.

The measurement of the crystal size distribution is a key prerequisite in optimising the growth of sugar crystals in crystalisation pans or for quality control of the final product. Traditionally, crystal size measurements are carried out by inspection or using mechanical sieves. Apart from being time consuming, these techniques can only provide limited quantitative information. For this reason, a more quantitative automatic system is required. In our project, software routines for the automated measurement of crystal size using classical image analysis techniques were developed. A digital imaging technique involves automatically analyzing a captured image of a representative sample of ~ 100 crystals for the automated measurement of crystal size has been developed. The main problem of crystals size measurements using image processing is the lack of an efficient algorithm to identify and separate overlapping and touching crystals which otherwise compromise the accuracy of size measurement. This problem of overlapping and touching crystals was addressed in two ways. First, 5 algorithms which identify and separate overlapping and touching crystals, using mathematical morphology as a tool, were evaluated. The accuracy of the algorithms depends on the technique used to mark every crystal in the image. Secondly, another algorithm which used convexity measures of the crystals based on area and perimeter, to identify and reject overlapping and touching crystals, have been developed. Finally, the two crystal sizing algorithms, the one applies ultimate erosion followed by a distance transformation and the second uses convexity measures to identify overlapping crystals, were compared with well established mechanical sieving technique. Using samples obtained from a sugar refinery, the parameters of interest, including mean aperture (MA) and coefficient of variance (CV), were calculated and compared with those obtained from the sieving method. The imaging technique is faster, more reliable than sieving and can be used to measure the full crystal size distributions of both massecuite and dry product. / Thesis (PhD)-University of KwaZulu-Natal, Durban, 2007.

Orientadores: Carlos Roberto de Souza Filho, Laerte Guimarães Ferreira Junior / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Geociencias / Made available in DSpace on 2018-08-10T13:23:28Z (GMT). No. of bitstreams: 1 Nunes_GustavoManzon_D.pdf: 36857548 bytes, checksum: 70db72622f53387a3b3daa1b2a6ac19d (MD5) Previous issue date: 2008 / Resumo: O conhecimento da biodiversidade amazônica, em especial o relacionado à sua cobertura vegetal, tem sido alvo de amplos estudos envolvendo a investigação de seus processos ecológicos-evolutivos e o seu funcionamento como um conjunto integrado e complexo de unidades biológicas. O desenvolvimento de tecnologias e metodologias no campo do Sensoriamento Remoto, cada vez mais vem se tornando essencial na análise, discriminação e monitoramento de vastas áreas dominadas pela Floresta Tropical. Esta tese buscou avaliar os aspectos relacionados à potencialidade das imagens dos sensores Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)/Terra e Synthetic Aperture Radar (SAR)/R99-B, para a discriminação de fitofisionomias existentes nas Reservas de Desenvolvimento Sustentável Amanã e Mamirauá (RDSA e RDSM). A partir de processamentos realizados com os dados do sensor MODIS, Produto MOD13 ¿ Índices de Vegetação EVI (Enhanced vegetation ÍNDEX) e NDVI (Normalized Difference Vegetation Index), foi avaliado o comportamento sazonal/temporal de quatro fitofisionomias existentes nas RDSA e RDSM, entre os anos de 2004 e 2005. Com este estudo, foi possível concluir que (i) os índices de vegetação foram sensíveis às características estruturais e fisionômicas do geossistema estudado; (ii) o EVI apresentou a melhor resposta para a discriminação de fitofisionomias, (iii) é possível discriminar ¿endmembers¿ temporais para as distintas classes florestais, os quais podem servir como importantes referências para trabalhos futuros envolvendo a dinâmica da paisagem. Às imagens do sensor ASTER, nos intervalos espectrais do visível (0.52-0.69 µm), infravermelho próximo (0.78-0.86 µm) e infravermelho de ondas curtas (1.60 a 2.43 µm), foram aplicadas técnicas de classificação espectral adaptadas para os dados deste sensor (Spectral Angle Mapper (SAM) e Mixture Tuned Matched Filtering (MTMF)), além do NDVI. Através da técnica SAM foi possível a discriminação de seis fitofisionomias predominantes na RDSA. Através da técnica MTMF, que envolve um algoritmo de classificação mais robusto, informações equivalentes foram obtidas. Foi possível ainda a associação e detecção dos padrões espectrais da cobertura vegetal, mostrando a estreita relação com o índice NDVI. Utilizando-se dados do sensor aerotransportado SAR R99-B, adquiridos na banda L (1,28 GHz), em amplitude e com quatro polarizações (HH, VV, HV e VH), avaliou-se a distinção de fitofisionomias de floresta de várzea existentes em ambientes da RDSA e RDSM, com a aplicação do algoritmo Iterated Conditional Modes (ICM), de classificação polarimétrica pontual/contextual. Os resultados mostraram que o uso das distribuições multivariadas em amplitude, conjuntamente com uma banda de textura, produziu classificações de qualidade superior àquelas obtidas com dados polarimétricos uni/bivariados. Essa abordagem permitiu a discriminação correta de três classes vegetacionais de interesse, comprovando o potencial dos dados do SAR-SIPAM e do algoritmo ICM no mapeamento da cobertura vegetal da Amazônia / Abstract: The knowledge of the Amazon biodiversity, especially that related to its vegetation cover, has been the subject of several studies involving the investigation of its ecological-evolutional processes and its dynamics as an integrated and complex set of biological units. The development of Remote Sensing technologies and methodologies is becoming increasingly essential in the analysis and monitoring of vast areas dominated by the Amazon rainforest. Thus, this study seeks to evaluate the capability of data generated by the Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)/Terra and the Synthetic Aperture Radar (SAR)/R99-B sensors, in discriminating phytophysiognomies found in the Amanã and Mamirauá Sustainable Development Reserves (RDSA and RDSM). Product MOD13, derived from MODIS data processing, comprising the Vegetation Indices EVI (Enhanced vegetation Index) and NDVI (Normalized Difference Vegetation Index), was used to evaluate the seasonal/temporal behavior of four existing phytophysiognomies in RDSA and RDSM between 2004 and 2005. Results showed that (i) the vegetation indices were sensitive to the structural characteristics of the approached ecosystem and phytophysiognomies; (ii) the EVI index best discerned among the phytophysiognomies; (iii) temporal endmembers were distinguished for different classes of forests and may serve as important references for future work involving the dynamics of the landscape. ASTER data, including visible (0.52-0.69 µm), nearinfrared (0.78-0.86 µm) and shortwave infrared (1.60-2.43 µm) bands were processed through advanced spectral classification techniques, such as the Spectral Angle Mapper (SAM) e Mixture Tuned Matched Filtering (MTMF), besides NDVI. The SAM method allowed the recognition of six dominant phytophysiognomies in the RDSA. The MTMF, which involves a more robust spectral unmixing method, provided equivalent results. Using ASTER data, it was also possible to demonstrate the close relation between the spectral patterns and the NDVI values for the vegetation cover. By means of L band (1.28 GHz), full polarimetric (HH, VV, VH, HV), SAR-amplitude data acquired with the SAR R99-B sensor, distinctions among flooded forest phytophysiognomies in the RDSA and RDSM was pursued. The Iterated Conditional Modes (ICM) algorithm was employed to perform the local/contextual polarimetric classification of the data. Results showed that the use of multivariate distributions in amplitude with a band of texture produced classifications of superior quality in relation to those obtained with the uni / bivariate polarimetric data. This approach allowed the correct discrimination of three vegetation classes of interest, proving the potential of the SAR data and the algorithm ICM in forest mapping in the Amazon / Doutorado / Análise Ambiental e Dinâmica Territorial / Doutor em Geografia