Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Probiotic interventions in infancy: Benefit and Safety Assessment of Extended Applications

Immaturity of the gut barrier system in the newborn has been seen to underlie a number of chronic diseases originating in infancy and manifesting later in life. The gut microbiota and breast milk provide the most important maturing signals for the gut-related immune system and reinforcement of the gut mucosal barrier function. Recently, the composition of the gut microbiota has been proposed to be instrumental in control of host body weight and metabolism as well as the inflammatory state characterizing overweight and obesity. On this basis, inflammatory Western lifestyle diseases, including overweight development, may represent a potential target for probiotic interventions beyond the well documented clinical applications. The purpose of the present undertaking was to study the efficacy and safety of perinatal probiotic intervention. The material comprised two ongoing, prospective, double-blind NAMI (Nutrition, Allergy, Mucosal immunology and Intestinal microbiota) probiotic interventions. In the mother-infant nutrition and probiotic study altogether 256 women were randomized at their first trimester of pregnancy into a dietary intervention and a control group. The intervention group received intensive dietary counselling provided by a nutritionist, and were further randomized at baseline, double-blind, to receive probiotics (Lactobacillus rhamnosus GG and Bifidobacterium lactis) or placebo. The intervention period extended from the first trimester of pregnancy to the end of exclusive breastfeeding. In the allergy prevention study altogether 159 women were randomized, double-blind, to receive probiotics (Lactobacillus rhamnosus GG) or placebo 4 weeks before expected delivery, the intervention extending for 6 months postnatally. Additionally, patient data on all premature infants with very low birth weight (VLBW) treated in the Department of Paediatrics, Turku University Hospital, during the years 1997 - 2008 were utilized. The perinatal probiotic intervention reduced the risk of gestational diabetes mellitus (GDM) in the mothers and perinatal dietary counselling reduced that of fetal overgrowth in GDM-affected pregnancies. Early gut microbiota modulation with probiotics modified the growth pattern of the child by restraining excessive weight gain during the first years of life. The colostrum adiponectin concentration was demonstrated to be dependent on maternal diet and nutritional status during pregnancy. It was also higher in the colostrum received by normal-weight compared to overweight children at the age of 10 years. The early perinatal probiotic intervention and the postnatal probiotic intervention in VLBW infants were shown to be safe. To conclude, the findings in this study provided clinical evidence supporting the involvement of the initial microbial and nutritional environment in metabolic programming of the child. The manipulation of early gut microbial communities with probiotics might offer an applicable strategy to impact individual energy homeostasis and thus to prevent excessive body-weight gain. The results add weight to the hypothesis that interventions aiming to prevent obesity and its metabolic consequences later in life should be initiated as early as during the perinatal period.

Local and Global Feature Extraction for Invariant Object Recognition

Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

A modified structural stress method for fatigue assessment of welded structures

Fatigue life assessment of weldedstructures is commonly based on the nominal stress method, but more flexible and accurate methods have been introduced. In general, the assessment accuracy is improved as more localized information about the weld is incorporated. The structural hot spot stress method includes the influence of macro geometric effects and structural discontinuities on the design stress but excludes the local features of the weld. In this thesis, the limitations of the structural hot spot stress method are discussed and a modified structural stress method with improved accuracy is developed and verified for selected welded details. The fatigue life of structures in the as-welded state consists mainly of crack growth from pre-existing cracks or defects. Crack growth rate depends on crack geometry and the stress state on the crack face plane. This means that the stress level and shape of the stress distribution in the assumed crack path governs thetotal fatigue life. In many structural details the stress distribution is similar and adequate fatigue life estimates can be obtained just by adjusting the stress level based on a single stress value, i.e., the structural hot spot stress. There are, however, cases for which the structural stress approach is less appropriate because the stress distribution differs significantly from the more common cases. Plate edge attachments and plates on elastic foundations are some examples of structures with this type of stress distribution. The importance of fillet weld size and weld load variation on the stress distribution is another central topic in this thesis. Structural hot spot stress determination is generally based on a procedure that involves extrapolation of plate surface stresses. Other possibilities for determining the structural hot spot stress is to extrapolate stresses through the thickness at the weld toe or to use Dong's method which includes through-thickness extrapolation at some distance from the weld toe. Both of these latter methods are less sensitive to the FE mesh used. Structural stress based on surface extrapolation is sensitive to the extrapolation points selected and to the FE mesh used near these points. Rules for proper meshing, however, are well defined and not difficult to apply. To improve the accuracy of the traditional structural hot spot stress, a multi-linear stress distribution is introduced. The magnitude of the weld toe stress after linearization is dependent on the weld size, weld load and plate thickness. Simple equations have been derived by comparing assessment results based on the local linear stress distribution and LEFM based calculations. The proposed method is called the modified structural stress method (MSHS) since the structural hot spot stress (SHS) value is corrected using information on weld size andweld load. The correction procedure is verified using fatigue test results found in the literature. Also, a test case was conducted comparing the proposed method with other local fatigue assessment methods.

A Study on Fractionation and Ultrafiltration of Proteins with Characterized Modified and Unmodified Membranes

Membrane filtration has become increasingly attractive in the processing of both foodand biotechnological products. However, the poor selectivity of the membranes and fouling are the critical factors limiting the development of UF systems for the specific fractionation of protein mixtures. This thesis gives an overview on fractionation of proteins from model protein solutions or from biological solutions. An attempt was made to improve the selectivity of the available membranes by modifying the membranes and by exploiting the different electrostatic interactions between the proteins and the membrane pore surfaces. Fractionation and UF behavior of proteins in the model solutions and in the corresponding biological solutions were compared. Characterization of the membranes and protein adsorptionto the membrane were investigated with combined flux and streaming potential studies. It has been shown that fouling of the membranes can be reduced using "self-rejecting" membranes at pH values where electrostatic repulsion is achieved between the membrane and the proteins in solution. This effect is best shown in UF of dilute single protein solutions at low ionic strengths and low pressures. Fractionation of model proteins in single, binary, and ternary solutionshas been carried out. The results have been compared to the results obtained from fractination of biological solutions. It was generally observed that fractination of proteins from biological solutions are more difficult to carry out owingto the presence of non studied protein components with different properties. Itcan be generally concluded that it is easier to enrich the smaller protein in the permeate but it is also possible to enrich the larger protein in the permeateat pH values close to the isoelectric point of the protein. It should be possible to find an optimal flux and modification to effectively improve the fractination of proteins even with very similar molar masses.

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

A Practical Micro Mechanical Model Based Local Approach Methodology for the Analysis of Ductile Fracture of Welded T-Joints

This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

Plant-Herbivore Interaction in a Fragmented Landscape: Local Adaptation and Inbreeding

Reciprocal selection between interacting species is a major driver of biodiversity at both the genetic and the species level. This reciprocal selection, or coevolution, has led to the diversification of two highly diverse and abundant groups of organisms, flowering plants and their insect herbivores. In heterogeneous environments, the outcome of coevolved species interactions is influenced by the surrounding community and/or the abiotic environment. The process of adaptation allows species to adapt to their local conditions and to local populations of interacting species. However, adaptation can be disrupted or slowed down by an absence of genetic variation or by increased inbreeding, together with the following inbreeding depression, both of which are common in small and isolated populations that occur in fragmented environments. I studied the interaction between a long-lived plant Vincetoxicum hirundinaria and its specialist herbivore Abrostola asclepiadis in the southwestern archipelago of Finland. I focused on mutual local adaptation of plants and herbivores, which is a demonstration of reciprocal selection between species, a prerequisite for coevolution. I then proceeded to investigate the processes that could potentially hamper local adaptation, or species interaction in general, when the population size is small. I did this by examining how inbreeding of both plants and herbivores affects traits that are important for interaction, as well as among-population variation in the effects of inbreeding. In addition to bi-parental inbreeding, in plants inbreeding can arise from self-fertilization which has important implications for mating system evolution. I found that local adaptation of the plant to its herbivores varied among populations. Local adaptation of the herbivore varied among populations and years, being weaker in populations that were most connected. Inbreeding caused inbreeding depression in both plants and herbivores. In some populations inbreeding depression in herbivore biomass was stronger in herbivores feeding on inbred plants than in those feeding on outbred ones. For plants it was the other way around: inbreeding depression in anti-herbivore resistance decreased when the herbivores were inbred. Underlying some of the among-population variation in the effects of inbreeding is variation in plant phenolic compounds. However, variation in the modification of phenolic compounds in the digestive tract of the herbivore did not explain the inbreeding depression in herbivore biomass. Finally, adult herbivores had a preference for outbred host plants for egg deposition, and herbivore inbreeding had a positive effect on egg survival when the eggs were exposed to predators and parasitoids. These results suggest that plants and herbivores indeed exert reciprocal selection, as demonstrated by the significant local adaptation of V. hirundinaria and A. asclepiadis to one another. The most significant cause of disruption of the local adaptation of herbivore populations was population connectivity, and thus probably gene flow. In plants local adaptation tended to increase with increasing genetic variation. Whether or not inbreeding depression occurred varied according to the life-history stage of the herbivore and/or the plant trait in question. In addition, the effects of inbreeding strongly depended on the population. Taken together, inbreeding modified plant-herbivore interactions at several different levels, and can thus affect the strength of reciprocal selection between species. Thus inbreeding has the potential to affect the outcome of coevolution.

A modified nominal stress method for fatigue assessment of steel plates with thermally cut edges

Thermal cutting methods, are commonly used in the manufacture of metal parts. Thermal cutting processes separate materials by using heat. The process can be done with or without a stream of cutting oxygen. Common processes are Oxygen, plasma and laser cutting. It depends on the application and material which cutting method is used. Numerically-controlled thermal cutting is a cost-effective way of prefabricating components. One design aim is to minimize the number of work steps in order to increase competitiveness. This has resulted in the holes and openings in plate parts manufactured today being made using thermal cutting methods. This is a problem from the fatigue life perspective because there is local detail in the as-welded state that causes a rise in stress in a local area of the plate. In a case where the static utilization of a net section is full used, the calculated linear local stresses and stress ranges are often over 2 times the material yield strength. The shakedown criteria are exceeded. Fatigue life assessment of flame-cut details is commonly based on the nominal stress method. For welded details, design standards and instructions provide more accurate and flexible methods, e.g. a hot-spot method, but these methods are not universally applied to flame cut edges. Some of the fatigue tests of flame cut edges in the laboratory indicated that fatigue life estimations based on the standard nominal stress method can give quite a conservative fatigue life estimate in cases where a high notch factor was present. This is an undesirable phenomenon and it limits the potential for minimizing structure size and total costs. A new calculation method is introduced to improve the accuracy of the theoretical fatigue life prediction method of a flame cut edge with a high stress concentration factor. Simple equations were derived by using laboratory fatigue test results, which are published in this work. The proposed method is called the modified FAT method (FATmod). The method takes into account the residual stress state, surface quality, material strength class and true stress ratio in the critical place.