Multispectral image compression using the wavelet transform

Multispectral images contain information from several spectral wavelengths and currently multispectral images are widely used in remote sensing and they are becoming more common in the field of computer vision and in industrial applications. Typically, one multispectral image in remote sensing may occupy hundreds of megabytes of disk space and several this kind of images may be received from a single measurement. This study considers the compression of multispectral images. The lossy compression is based on the wavelet transform and we compare the suitability of different waveletfilters for the compression. A method for selecting a wavelet filter for the compression and reconstruction of multispectral images is developed. The performance of the multidimensional wavelet transform based compression is compared to other compression methods like PCA, ICA, SPIHT, and DCT/JPEG. The quality of the compression and reconstruction is measured by quantitative measures like signal-to-noise ratio. In addition, we have developed a qualitative measure, which combines the information from the spatial and spectral dimensions of a multispectral image and which also accounts for the visual quality of the bands from the multispectral images.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.

Measuring irregularities and surface defects from printed patterns

Quality inspection and assurance is a veryimportant step when today's products are sold to markets. As products are produced in vast quantities, the interest to automate quality inspection tasks has increased correspondingly. Quality inspection tasks usuallyrequire the detection of deficiencies, defined as irregularities in this thesis. Objects containing regular patterns appear quite frequently on certain industries and science, e.g. half-tone raster patterns in the printing industry, crystal lattice structures in solid state physics and solder joints and components in the electronics industry. In this thesis, the problem of regular patterns and irregularities is described in analytical form and three different detection methods are proposed. All the methods are based on characteristics of Fourier transform to represent regular information compactly. Fourier transform enables the separation of regular and irregular parts of an image but the three methods presented are shown to differ in generality and computational complexity. Need to detect fine and sparse details is common in quality inspection tasks, e.g., locating smallfractures in components in the electronics industry or detecting tearing from paper samples in the printing industry. In this thesis, a general definition of such details is given by defining sufficient statistical properties in the histogram domain. The analytical definition allowsa quantitative comparison of methods designed for detail detection. Based on the definition, the utilisation of existing thresholding methodsis shown to be well motivated. Comparison of thresholding methods shows that minimum error thresholding outperforms other standard methods. The results are successfully applied to a paper printability and runnability inspection setup. Missing dots from a repeating raster pattern are detected from Heliotest strips and small surface defects from IGT picking papers.

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

Level Set Methods in Image Processing

This thesis gives an overview of the use of the level set methods in the field of image science. The similar fast marching method is discussed for comparison, also the narrow band and the particle level set methods are introduced. The level set method is a numerical scheme for representing, deforming and recovering structures in an arbitrary dimensions. It approximates and tracks the moving interfaces, dynamic curves and surfaces. The level set method does not define how and why some boundary is advancing the way it is but simply represents and tracks the boundary. The principal idea of the level set method is to represent the N dimensional boundary in the N+l dimensions. This gives the generality to represent even the complex boundaries. The level set methods can be powerful tools to represent dynamic boundaries, but they can require lot of computing power. Specially the basic level set method have considerable computational burden. This burden can be alleviated with more sophisticated versions of the level set algorithm like the narrow band level set method or with the programmable hardware implementation. Also the parallel approach can be used in suitable applications. It is concluded that these methods can be used in a quite broad range of image applications, like computer vision and graphics, scientific visualization and also to solve problems in computational physics. Level set methods and methods derived and inspired by it will be in the front line of image processing also in the future.

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.

Spektrikuvien tiivistäminen itseorganisoituvan kartan avulla.

Vuosi vuodelta kasvava tietokoneiden prosessointikyky on mahdollistanut harmaataso- ja RGB-värikuvia tarkempien spektrikuvien käsittelyn järjellisessä ajassa ilman suuria kustannuksia. Ongelmana on kuitenkin, ettei talletus- ja tiedonsiirtomedia ole kehittynyt prosessointikyvyn vauhdissa. Ratkaisu tähän ongelmaan on spektrikuvien tiivistäminen talletuksen ja tiedonsiirron ajaksi. Tässä työssä esitellään menetelmä, jossa spektrikuva tiivistetään kahdessa vaiheessa: ensin ryhmittelemällä itseorganisoituvan kartan (SOM) avulla ja toisessa vaiheessa jatketaan tiivistämistä perinteisin menetelmin. Saadut tiivistyssuhteet ovat merkittäviä vääristymän pysyessä siedettävänä. Työ on tehty Lappeenrannan teknillisen korkeakoulun Tietotekniikan osaston Tietojenkäsittelytekniikan tutkimuslaboratoriossa osana laajempaa kuvantiivistyksen tutkimushanketta.

Reconstruction of 3D Planar Objects with Partial Occlusion

Kolmiulotteisten kappaleiden rekonstruktio on yksi konenäön haastavimmista ongelmista, koska kappaleiden kolmiulotteisia etäisyyksiä ei voida selvittää yhdestä kaksiulotteisesta kuvasta. Ongelma voidaan ratkaista stereonäön avulla, jossa näkymän kolmiulotteinen rakenne päätellään usean kuvan perusteella. Tämä lähestymistapa mahdollistaa kuitenkin vain rekonstruktion niille kappaleiden osille, jotka näkyvät vähintään kahdessa kuvassa. Piilossa olevien osien rekonstruktio ei ole mahdollista pelkästään stereonäön avulla. Tässä työssä on kehitetty uusi menetelmä osittain piilossa olevien kolmiulotteisten tasomaisten kappaleiden rekonstruktioon. Menetelmän avulla voidaan selvittää hyvällä tarkkuudella tasomaisista pinnoista koostuvan kappaleen muoto ja paikka käyttäen kahta kuvaa kappaleesta. Menetelmä perustuu epipolaarigeometriaan, jonka avulla selvitetään molemmissa kuvissa näkyvät kappaleiden osat. Osittain piilossa olevien piirteiden rekonstruointi suoritetaan käyttämäen stereonäköä sekä tietoa kappaleen rakenteesta. Esitettyä ratkaisua voitaisiin käyttää esimerkiksi kolmiulotteisten kappaleiden visualisointiin, robotin navigointiin tai esineentunnistukseen.

Visual signs and symptoms in patients with the visual variant of Alzheimer disease.

BACKGROUND: Prominent visual symptoms can present in the visual variant of Alzheimer's disease (VVAD). Ophthalmologists have a significant role to play in the early diagnosis of VVAD. METHODS: We retrospectively reviewed the files of ten consecutive patients diagnosed with VVAD. All patients had a full neuro-ophthalmologic examination, a formal neurological and neuro-psychological testing, and cerebral MRI to confirm diagnosis. In addition, functional neuroimaging was obtained in seven patients. RESULTS: The common primary symptom at presentation with all patients was difficulty with near vision (reading difficulty n = 8, "visual blur" in near vision n = 2), and difficulty writing (n = 3). Following assessment, impaired reading and writing skills were evident in 9/10 and 8/10 patients respectively. Median distance visual acuity was 20/25 and at near the median visual acuity was J6. Partial homonymous visual field defect was detected in 80 % (8/10) of the patients. Color vision was impaired in all patients when tested with Ishihara pseudoisochromatic plates, but simple color naming was normal in 8/9 tested patients. Simultanagnosia was present in 8/10 patients. Vision dysfunction corresponded with cerebral MRI findings where parieto-occipital cortical atrophy was observed in all patients. PET scan (5 patients) or SPECT (2 patients) revealed parieto-occipital dysfunction (hypometabolism or hypoperfusion) in all 7 tested patients CONCLUSIONS: Visual difficulties are prominent in VVAD. Dyslexia, incomplete homonymous hemianopia, preserved color identification with abnormal color vision on Ishihara, and simultanagnosia were all symptoms observed frequently in this patient series. Ophthalmologists should be aware of the possibility of neurodegenerative disorders such as VVAD in patients with unexplained visual complaints, in particular reading difficulties.

Responding to Young People's Health Risks in Primary Care: A Cluster Randomised Trial of Training Clinicians in Screening and Motivational Interviewing.

OBJECTIVE: To evaluate the effectiveness of a complex intervention implementing best practice guidelines recommending clinicians screen and counsel young people across multiple psychosocial risk factors, on clinicians' detection of health risks and patients' risk taking behaviour, compared to a didactic seminar on young people's health. DESIGN: Pragmatic cluster randomised trial where volunteer general practices were stratified by postcode advantage or disadvantage score and billing type (private, free national health, community health centre), then randomised into either intervention or comparison arms using a computer generated random sequence. Three months post-intervention, patients were recruited from all practices post-consultation for a Computer Assisted Telephone Interview and followed up three and 12 months later. Researchers recruiting, consenting and interviewing patients and patients themselves were masked to allocation status; clinicians were not. SETTING: General practices in metropolitan and rural Victoria, Australia. PARTICIPANTS: General practices with at least one interested clinician (general practitioner or nurse) and their 14-24 year old patients. INTERVENTION: This complex intervention was designed using evidence based practice in learning and change in clinician behaviour and general practice systems, and included best practice approaches to motivating change in adolescent risk taking behaviours. The intervention involved training clinicians (nine hours) in health risk screening, use of a screening tool and motivational interviewing; training all practice staff (receptionists and clinicians) in engaging youth; provision of feedback to clinicians of patients' risk data; and two practice visits to support new screening and referral resources. Comparison clinicians received one didactic educational seminar (three hours) on engaging youth and health risk screening. OUTCOME MEASURES: Primary outcomes were patient report of (1) clinician detection of at least one of six health risk behaviours (tobacco, alcohol and illicit drug use, risks for sexually transmitted infection, STI, unplanned pregnancy, and road risks); and (2) change in one or more of the six health risk behaviours, at three months or at 12 months. Secondary outcomes were likelihood of future visits, trust in the clinician after exit interview, clinician detection of emotional distress and fear and abuse in relationships, and emotional distress at three and 12 months. Patient acceptability of the screening tool was also described for the intervention arm. Analyses were adjusted for practice location and billing type, patients' sex, age, and recruitment method, and past health risks, where appropriate. An intention to treat analysis approach was used, which included multilevel multiple imputation for missing outcome data. RESULTS: 42 practices were randomly allocated to intervention or comparison arms. Two intervention practices withdrew post allocation, prior to training, leaving 19 intervention (53 clinicians, 377 patients) and 21 comparison (79 clinicians, 524 patients) practices. 69% of patients in both intervention (260) and comparison (360) arms completed the 12 month follow-up. Intervention clinicians discussed more health risks per patient (59.7%) than comparison clinicians (52.7%) and thus were more likely to detect a higher proportion of young people with at least one of the six health risk behaviours (38.4% vs 26.7%, risk difference [RD] 11.6%, Confidence Interval [CI] 2.93% to 20.3%; adjusted odds ratio [OR] 1.7, CI 1.1 to 2.5). Patients reported less illicit drug use (RD -6.0, CI -11 to -1.2; OR 0·52, CI 0·28 to 0·96), and less risk for STI (RD -5.4, CI -11 to 0.2; OR 0·66, CI 0·46 to 0·96) at three months in the intervention relative to the comparison arm, and for unplanned pregnancy at 12 months (RD -4.4; CI -8.7 to -0.1; OR 0·40, CI 0·20 to 0·80). No differences were detected between arms on other health risks. There were no differences on secondary outcomes, apart from a greater detection of abuse (OR 13.8, CI 1.71 to 111). There were no reports of harmful events and intervention arm youth had high acceptance of the screening tool. CONCLUSIONS: A complex intervention, compared to a simple educational seminar for practices, improved detection of health risk behaviours in young people. Impact on health outcomes was inconclusive. Technology enabling more efficient, systematic health-risk screening may allow providers to target counselling toward higher risk individuals. Further trials require more power to confirm health benefits. TRIAL REGISTRATION: ISRCTN.com ISRCTN16059206.

Prosessitietokoneen käytön kehittäminen Mertaniemen voimalaitoksella

Mertaniemen voimalaitoksien prosessitietokone (PTK) on uusittu keväällä 2005. Tämän työn tarkoituksena on ollut auttaa PTK:n virheiden korjaamisessa ja puut-teiden kartoittamisessa. Työssä on keskitytty etenkin prosessiraportoinnin tekemiseen. Työn alussa on kerrottu Mertaniemen voimalaitoksen tekniset tiedot ja PTK:n hankinnan taustatietoja. Uudesta PTK-järjestelmästä on kuvattu laitteisto, sovellus ja perusohjelmistot. PTK:n ja muiden järjestelmien välinen tiedonsiirto on myös kuvattu. PTK muuttujien nimeäminen on esitelty, jotta olisi helpompi hahmottaa työssä käytettyjen positioiden merkityksiä. Prosessiraportoinnin kehittämisessä kuvataan raporttien tarvetta ja niiden sisältöä sekä sitä kuinka raportit on tehty. Päästöraportointi on esitetty omana osa-alueenaan, koska voimalaitosten päästöjen seurantaa edellytetään tehtävän viran¬omaismääräysten ja EU-direktiivien vaatimusten mukaisesti. Raporttien lisäksi prosessiarvojen seuraamista helpottamaan on tehty yhteisiä trendi- ja työtilanäyttöjä. PTK:n ongelmakohtina on käsitelty muuttujien tunnuksissa ja nimissä olevat virheet sekä PTK laskennan tarkastaminen. Muuttujien nimien ja laskennan tarkas¬tusta tehtiin prosessiraportoinnin tekemisen yhteydessä sekä yhteistyössä PTK-järjestelmän toimittaneen Metso Automation Oy:n kanssa. Päästölaskennan korjaaminen oli erityisen tärkeää.

Improving anterior deltoid activity in a musculoskeletal shoulder model - an analysis of the torque-feasible space at the sternoclavicular joint.

Modelling the shoulder's musculature is challenging given its mechanical and geometric complexity. The use of the ideal fibre model to represent a muscle's line of action cannot always faithfully represent the mechanical effect of each muscle, leading to considerable differences between model-estimated and in vivo measured muscle activity. While the musculo-tendon force coordination problem has been extensively analysed in terms of the cost function, only few works have investigated the existence and sensitivity of solutions to fibre topology. The goal of this paper is to present an analysis of the solution set using the concepts of torque-feasible space (TFS) and wrench-feasible space (WFS) from cable-driven robotics. A shoulder model is presented and a simple musculo-tendon force coordination problem is defined. The ideal fibre model for representing muscles is reviewed and the TFS and WFS are defined, leading to the necessary and sufficient conditions for the existence of a solution. The shoulder model's TFS is analysed to explain the lack of anterior deltoid (DLTa) activity. Based on the analysis, a modification of the model's muscle fibre geometry is proposed. The performance with and without the modification is assessed by solving the musculo-tendon force coordination problem for quasi-static abduction in the scapular plane. After the proposed modification, the DLTa reaches 20% of activation.

Laboratory automation in clinical bacteriology: what system to choose?

Automation was introduced many years ago in several diagnostic disciplines such as chemistry, haematology and molecular biology. The first laboratory automation system for clinical bacteriology was released in 2006, and it rapidly proved its value by increasing productivity, allowing a continuous increase in sample volumes despite limited budgets and personnel shortages. Today, two major manufacturers, BD Kiestra and Copan, are commercializing partial or complete laboratory automation systems for bacteriology. The laboratory automation systems are rapidly evolving to provide improved hardware and software solutions to optimize laboratory efficiency. However, the complex parameters of the laboratory and automation systems must be considered to determine the best system for each given laboratory. We address several topics on laboratory automation that may help clinical bacteriologists to understand the particularities and operative modalities of the different systems. We present (a) a comparison of the engineering and technical features of the various elements composing the two different automated systems currently available, (b) the system workflows of partial and complete laboratory automation, which define the basis for laboratory reorganization required to optimize system efficiency, (c) the concept of digital imaging and telebacteriology, (d) the connectivity of laboratory automation to the laboratory information system, (e) the general advantages and disadvantages as well as the expected impacts provided by laboratory automation and (f) the laboratory data required to conduct a workflow assessment to determine the best configuration of an automated system for the laboratory activities and specificities.

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach