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.

Distance Transforms on Gray-Level Surfaces

This thesis studies gray-level distance transforms, particularly the Distance Transform on Curved Space (DTOCS). The transform is produced by calculating distances on a gray-level surface. The DTOCS is improved by definingmore accurate local distances, and developing a faster transformation algorithm. The Optimal DTOCS enhances the locally Euclidean Weighted DTOCS (WDTOCS) with local distance coefficients, which minimize the maximum error from the Euclideandistance in the image plane, and produce more accurate global distance values.Convergence properties of the traditional mask operation, or sequential localtransformation, and the ordered propagation approach are analyzed, and compared to the new efficient priority pixel queue algorithm. The Route DTOCS algorithmdeveloped in this work can be used to find and visualize shortest routes between two points, or two point sets, along a varying height surface. In a digital image, there can be several paths sharing the same minimal length, and the Route DTOCS visualizes them all. A single optimal path can be extracted from the route set using a simple backtracking algorithm. A new extension of the priority pixel queue algorithm produces the nearest neighbor transform, or Voronoi or Dirichlet tessellation, simultaneously with the distance map. The transformation divides the image into regions so that each pixel belongs to the region surrounding the reference point, which is nearest according to the distance definition used. Applications and application ideas for the DTOCS and its extensions are presented, including obstacle avoidance, image compression and surface roughness evaluation.

Towards desired crystalline product properties: In-situ monitoring of batch crystallization

The objective of industrial crystallization is to obtain a crystalline product which has the desired crystal size distribution, mean crystal size, crystal shape, purity, polymorphic and pseudopolymorphic form. Effective control of the product quality requires an understanding of the thermodynamics of the crystallizing system and the effects of operation parameters on the crystalline product properties. Therefore, obtaining reliable in-line information about crystal properties and supersaturation, which is the driving force of crystallization, would be very advantageous. Advanced techniques, such asRaman spectroscopy, attenuated total reflection Fourier transform infrared (ATR FTIR) spectroscopy, and in-line imaging techniques, offer great potential for obtaining reliable information during crystallization, and thus giving a better understanding of the fundamental mechanisms (nucleation and crystal growth) involved. In the present work, the relative stability of anhydrate and dihydrate carbamazepine in mixed solvents containing water and ethanol were investigated. The kinetics of the solvent mediated phase transformation of the anhydrate to hydrate in the mixed solvents was studied using an in-line Raman immersion probe. The effects of the operation parameters in terms of solvent composition, temperature and the use of certain additives on the phase transformation kineticswere explored. Comparison of the off-line measured solute concentration and the solid-phase composition measured by in-line Raman spectroscopy allowedthe identification of the fundamental processes during the phase transformation. The effects of thermodynamic and kinetic factors on the anhydrate/hydrate phase of carbamazepine crystals during cooling crystallization were also investigated. The effect of certain additives on the batch cooling crystallization of potassium dihydrogen phosphate (KDP) wasinvestigated. The crystal growth rate of a certain crystal face was determined from images taken with an in-line video microscope. An in-line image processing method was developed to characterize the size and shape of thecrystals. An ATR FTIR and a laser reflection particle size analyzer were used to study the effects of cooling modes and seeding parameters onthe final crystal size distribution of an organic compound C15. Based on the obtained results, an operation condition was proposed which gives improved product property in terms of increased mean crystal size and narrowersize distribution.

Keraamisten laattojen luokittelu väripiirteiden avulla

Vaikka keraamisten laattojen valmistusprosessi onkin täysin automatisoitu, viimeinen vaihe eli laaduntarkistus ja luokittelu tehdään yleensä ihmisvoimin. Automaattinen laaduntarkastus laattojen valmistuksessa voidaan perustella taloudellisuus- ja turvallisuusnäkökohtien avulla. Tämän työn tarkoituksena on kuvata tutkimusprojektia keraamisten laattojen luokittelusta erilaisten väripiirteiden avulla. Oleellisena osana tutkittiin RGB- ja spektrikuvien välistä eroa. Työn teoreettinen osuus käy läpi aiemmin aiheesta tehdyn tutkimuksen sekä antaa taustatietoa konenäöstä, hahmontunnistuksesta, luokittelijoista sekä väriteoriasta. Käytännön osan aineistona oli 25 keraamista laattaa, jotka olivat viidestä eri luokasta. Luokittelussa käytettiin apuna k:n lähimmän naapurin (k-NN) luokittelijaa sekä itseorganisoituvaa karttaa (SOM). Saatuja tuloksia verrattiin myös ihmisten tekemään luokitteluun. Neuraalilaskenta huomattiin tärkeäksi työkaluksi spektrianalyysissä. SOM:n ja spektraalisten piirteiden avulla saadut tulokset olivat lupaavia ja ainoastaan kromatisoidut RGB-piirteet olivat luokittelussa parempia kuin nämä.

Huulisuihkun homogeenisuuden vaikutus paperin rakenneominaisuuksiin

Työssä verrattiin perälaatikoilla 1 ja 2 valmistettujen papereiden rakenteellisia ominaisuuksia. Paperin rakenteessa formaatio oli tärkein ominaisuus ja sen jälkeen kuituorientaatio. Näytteiden valintaperusteena pidettiin sitä, että vertailtavilla näytteillä formaatio (pohja) oli paras kyseisellä perälaatikolla ja vetolujuussuhteet olivat samoja. Toinen valintatapa oli verrata samoissa virtausolosuhteissa valmistettuja papereita keskenään. Näytteiden formaatio mitattiin betaradiografialla. Fosforikuvalevystä skannattu kuva analysoitiin kuva-analyysillä. Mittauksen etuna oli suuri erottelukyky, joka mahdollisti monipuolisen tunnuslukujen laskennan. Näistä esimerkkeinä olivat keskihajonta, vinous ja huipukkuus. Lisäksi määritettiin flokkikokojakaumat sekä kone- että poikkisuuntaan. Kuituorientaation määrityksessä paperinäyte revittiin kerroksiin, kerrokset skannattiin ja kuvat analysoitiin kuvankäsittelyohjelmilla. Juova- ja kuituorientaatioanalyysissä määritettiin orientaatiokulma, max/min-arvo ja anisotropia. Virtaviiva-analyysin tunnusluku oli pyörrekoko. Käytettäessä tunnuslukuna variaatiokerrointa formaatio oli parempi perälaatikolla 1 ali- ja yliperällä. Tasaperän läheisyydessä formaatio oli huonompi. Keskihajonta oli pienempi perälaatikolla 1, mutta erot perälaatikoiden välillä tasaantuivat lähellä tasaperää. Flokkikoko oli koko s/v-alueella hieman suurempi perälaatikolla 1. Virtaviiva-analyysin avulla saatiin selville, että perälaatikolla 1 valmistettujen papereiden paikallinen orientaatiovaihtelu ja pintojen toispuoleisuus oli lievempää kuin perälaatikolla 2.

The influence of crystallization conditions on the filtration characteristics of sulphathiazole suspensions

Cooling crystallization is one of the most important purification and separation techniques in the chemical and pharmaceutical industry. The product of the cooling crystallization process is always a suspension that contains both the mother liquor and the product crystals, and therefore the first process step following crystallization is usually solid-liquid separation. The properties of the produced crystals, such as their size and shape, can be affected by modifying the conditions during the crystallization process. The filtration characteristics of solid/liquid suspensions, on the other hand, are strongly influenced by the particle properties, as well as the properties of the liquid phase. It is thus obvious that the effect of the changes made to the crystallization parameters can also be seen in the course of the filtration process. Although the relationship between crystallization and filtration is widely recognized, the number of publications where these unit operations have been considered in the same context seems to be surprisingly small. This thesis explores the influence of different crystallization parameters in an unseeded batch cooling crystallization process on the external appearance of the product crystals and on the pressure filtration characteristics of the obtained product suspensions. Crystallization experiments are performed by crystallizing sulphathiazole (C9H9N3O2S2), which is a wellknown antibiotic agent, from different mixtures of water and n-propanol in an unseeded batch crystallizer. The different crystallization parameters that are studied are the composition of the solvent, the cooling rate during the crystallization experiments carried out by using a constant cooling rate throughout the whole batch, the cooling profile, as well as the mixing intensity during the batch. The obtained crystals are characterized by using an automated image analyzer and the crystals are separated from the solvent through constant pressure batch filtration experiments. Separation characteristics of the suspensions are described by means of average specific cake resistance and average filter cake porosity, and the compressibilities of the cakes are also determined. The results show that fairly large differences can be observed between the size and shape of the crystals, and it is also shown experimentally that the changes in the crystal size and shape have a direct impact on the pressure filtration characteristics of the crystal suspensions. The experimental results are utilized to create a procedure that can be used for estimating the filtration characteristics of solid-liquid suspensions according to the particle size and shape data obtained by image analysis. Multilinear partial least squares regression (N-PLS) models are created between the filtration parameters and the particle size and shape data, and the results presented in this thesis show that relatively obvious correlations can be detected with the obtained models.

Imaging and Characterisation of Dirt Particles in Pulp and Paper

Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.

Holocene Varved Lake Sediments as Records of Palaeoenvironmental Change and Geomagnetic Palaeosecular Variation in Eastern Finland

This dissertation discusses Holocene palaeoenvironmental and palaeomagnetic secular variation (PSV) records reconstructed from sediments preserved in Lake Lehmilampi (63º37´N, 29º06´E) and Lake Kortejärvi (63º37´N, 28º56´E) in eastern Finland. Several piston and freeze cores were obtained from both lakes for varve and magnetic analyses. Sediment samples were impregnated in low-viscosity epoxy and physical parameters of varves, including varve thickness and relative grey-scale values, were recorded using x-ray densitometry combined with semiautomatic digital image analysis. On average, varve records of Lehmilampi and Kortejärvi cover 5122 and 3902 years, respectively. Past solar activity, as estimated by residual ₁₄C data, compares favourably with varve thicknesses from Lehmilampi during the last 2000 years. This indicates the potential of clastic-organic varves to record sensitively climatic variations. Bulk magnetic parameters, including magnetic susceptibility together with natural, anhysteretic and isothermal remanent magnetizations, were measured to describe mineral magnetic properties and geomagnetic palaeosecular variation recorded in the sediments. Main stages in the development of the investigated lakes are reflected in the variations in the mineral magnetic records, sediment lithology and composition. Similar variations in magnetic parameters and sediment organic matter suggest contribution of bacterial magnetite in the magnetic assemblages of Lehmilampi. Inclination and relative declination records yielded largely consistent results, attesting to the great potential of these sediments to preserve directional palaeosecular variation in high resolution. The PSV data from Lehmilampi and Kortejärvi were stacked into North Karelian PSV stack, which may be used for dating homogenous lake sediments in the same regional context. Reconstructed millennial variations in relative palaeointensity results are approximately in agreement with those seen in the absolute palaeointensity data from Europe. Centennial variations in the relative palaeointensity, however, are influenced by environmental changes. Caution is recommended when using varved lake sediments in reconstructing relative palaeointensity.

Design of Installation for Transport Measurements

In the present work the aim was to prepare an automatic installation for studies of galvanomagnetic effects in solids and to test it by calibration measurements. As a result required automatic installation was created in this work and test measurements were performed. Created setup automatically provides measurements of the magnetoresistance of the Hall effect with an accuracy of ± 2 µV in the temperature range 2 – 300 K and steady magnetic fields up to 6 T. The test measurements of the glassy carbon samples showed that the setup is reliable, has high sensitivity and is easy to use. The results obtained in the research process are pioneer and will be separately analyzed.

Biopolttoaineiden leijutusominaisuuksien karakterisointi

Tässä diplomityössä selvitettiin biopolttoaineiden ominaisuuksia leijutuksen kannalta. Ensiksi tutkittavat biopolttoaineet, hake ja turve, seulottiin ja seulotut näytteet analysoitiin. Seuraavaksi turvetta ja haketta leijutettiin eri nopeuksilla ja eri leijutusnopeuksilla saadut näytteet analysoitiin kuva-analysilla. Partikkeleista selvitettiin runsaasti mittoja, kuten keskihalkaisija, pinta-ala ja muotokerroin. Kirjallisuudesta löytyvien korrelaatioiden avulla laskettiin leijutettujen partikkelien vastuskertoimet ja terminaalinopeudet. Korrelaatioiden tuloksia verrattiin mittaustuloksiin. Tässä työssä myös laskettiin kyseisiin biopolttoaineisiin vaikuttavat ominaisvoimat leijutuksessa sekä laskettiin korjauskerroin, jota käytettiin ominaisvoimien korjaamiseen. Referenssiaineina käytettiin hiekkaa ja lasikuulia.

A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

Challenges in scaling agile software development in offshoring environment

Corporate decision to scale Agile Software development methodologies in offshoring environment has been obstructed due to possible challenges in scaling agile as agile methodologies are regarded to be suitable for small project and co-located team only. Although model such as Agile Scaling Model (ASM) has been developed for scaling Agile with different factors, inabilities of companies to figure out challenges and addressing them lead to failure of project rather than gaining the benefits of using agile methodologies. This failure can be avoided, when scaling agile in IT offshoring environment, by determining key challenges associated in scaling agile in IT offshoring environment and then preparing strategies for addressing those key challenges. These key challenges in scaling agile with IT offshoring environment can be determined by studying issues related with Offshoring and Agile individually and also considering the positive impact of agile methodology in offshoring environment. Then, possible strategies to tackle these key challenges are developed according to the nature of individual challenges and utilizing the benefits of different agile methodologies to address individual situation. Thus, in this thesis, we proposed strategy of using hybrid agile method, which is increasing trend due to adaptive nature of Agile. Determination of the key challenges and possible strategies for tackling those challenges are supported with the survey conducted in the researched organization.

Evaluation of Bubble Formation and Break Up in Suppression Pools by Using Pattern Recognition Methods

During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.

Differentiation of Metabolically Distinct Areas within Head and Neck Region using Dynamic 18F-FDG Positron Emission Tomography Imaging

Positron Emission Tomography (PET) using ¹⁸F-FDG is playing a vital role in the diagnosis and treatment planning of cancer. However, the most widely used radiotracer, ¹⁸F-FDG, is not specific for tumours and can also accumulate in inflammatory lesions as well as normal physiologically active tissues making diagnosis and treatment planning complicated for the physicians. Malignant, inflammatory and normal tissues are known to have different pathways for glucose metabolism which could possibly be evident from different characteristics of the time activity curves from a dynamic PET acquisition protocol. Therefore, we aimed to develop new image analysis methods, for PET scans of the head and neck region, which could differentiate between inflammation, tumour and normal tissues using this functional information within these radiotracer uptake areas. We developed different dynamic features from the time activity curves of voxels in these areas and compared them with the widely used static parameter, SUV, using Gaussian Mixture Model algorithm as well as K-means algorithm in order to assess their effectiveness in discriminating metabolically different areas. Moreover, we also correlated dynamic features with other clinical metrics obtained independently of PET imaging. The results show that some of the developed features can prove to be useful in differentiating tumour tissues from inflammatory regions and some dynamic features also provide positive correlations with clinical metrics. If these proposed methods are further explored then they can prove to be useful in reducing false positive tumour detections and developing real world applications for tumour diagnosis and contouring.

Adopting the Vaadin Java framework to rebuild VTT’s Web Interfaces and Database Applications

With the growth in new technologies, using online tools have become an everyday lifestyle. It has a greater impact on researchers as the data obtained from various experiments needs to be analyzed and knowledge of programming has become mandatory even for pure biologists. Hence, VTT came up with a new tool, R Executables (REX) which is a web application designed to provide a graphical interface for biological data functions like Image analysis, Gene expression data analysis, plotting, disease and control studies etc., which employs R functions to provide results. REX provides a user interactive application for the biologists to directly enter the values and run the required analysis with a single click. The program processes the given data in the background and prints results rapidly. Due to growth of data and load on server, the interface has gained problems concerning time consumption, poor GUI, data storage issues, security, minimal user interactive experience and crashes with large amount of data. This thesis handles the methods by which these problems were resolved and made REX a better application for the future. The old REX was developed using Python Django and now, a new programming language, Vaadin has been implemented. Vaadin is a Java framework for developing web applications and the programming language is extremely similar to Java with new rich components. Vaadin provides better security, better speed, good and interactive interface. In this thesis, subset functionalities of REX was selected which includes IST bulk plotting and image segmentation and implemented those using Vaadin. A code of 662 lines was programmed by me which included Vaadin as the front-end handler while R language was used for back-end data retrieval, computing and plotting. The application is optimized to allow further functionalities to be migrated with ease from old REX. Future development is focused on including Hight throughput screening functions along with gene expression database handling