Automatic traffic sign inventory- and condition analysis

This thesis researches automatic traffic sign inventory and condition analysis using machine vision and pattern recognition methods. Automatic traffic sign inventory and condition analysis can be used to more efficient road maintenance, improving the maintenance processes, and to enable intelligent driving systems. Automatic traffic sign detection and classification has been researched before from the viewpoint of self-driving vehicles, driver assistance systems, and the use of signs in mapping services. Machine vision based inventory of traffic signs consists of detection, classification, localization, and condition analysis of traffic signs. The produced machine vision system performance is estimated with three datasets, from which two of have been been collected for this thesis. Based on the experiments almost all traffic signs can be detected, classified, and located and their condition analysed. In future, the inventory system performance has to be verified in challenging conditions and the system has to be pilot tested.

Repeatability in automatic sorting of curved Norway spruce saw logs

Abstract

Konenäköinvestoinnin soveltuvuus- ja esikannattavuustukimus sahalaitoksessa

Diplomityön tavoitteena oli selvittää sahalaitokselle mahdollisen konenäköinvestoinninsoveltuvuus ja kannattavuus. Tutkimus rajattiin vaihtoehtojen tunnistamisen ja investoinnin kannattavuuden alustavaan analyysiin. Tutkimuksessa arvioitiin konenäkötekniikan mahdollisuuksia sahateollisuusprosessissa yleisesti sekä erityisesti sahatavaran pitkittäis- ja poikittaissuuntaisissa sahatavaran pinnantarkastuksissa. Konenäköjärjestelmien toimittajia ja heidän referenssejään haastattelemalla saatiin selvitettyä tarjottujen järjestelmien tekninen soveltuvuus. Tutkimus liitettiin työn toimeksiantajan toimintastrategiaan, jotta voitiin arvioida mahdollisimman kattavasti kaikki investoinnilla saavutettavat hyödyt. Kannattavuuslaskentaa varten arvioitiin investoinnilla saavutettavat nettotuotot suunnitellulle pitoajalle. Laskennassa käytettiin perinteisiä investointilaskentamenetelmiä kuten nykyarvomenetelmää, takaisinmaksuaikaa ja sisäistä korkokantaa. Poikittaissuuntainen sahatavaran pinnantarkastus tuoreen ja kuivan tavaran tasaamolla todettiin teknisesti toteuttamiskelpoiseksi vaihtoehdoksi. Kyseisessä vaihtoehdossa liitännäisinvestointien määrän arvioidaan jäävän melko vähäisiksi. Konenäköinvestoinnin voidaan arvioida kannattavan, muttakannattavuuden edellytyksenä on vahva johdon ja muun henkilöstön sitoutuminen uuteen haasteeseen.

Metal surface and subsurface inspection using nondestructive optical methods

This thesis considers nondestructive optical methods for metal surface and subsurface inspection. The main purpose of this thesis was to study some optical methods in order to find out their applicability to industrial measurements. In laboratory testing the simplest light scattering approach, measurement of specular reflectance, was used for surface roughness evaluation. Surface roughness, curvature and finishing process of metal sheets were determined by specular reflectance measurements. Using a fixed angleof incidence, the specular reflectance method might be automated for industrialinspection. For defect detection holographic interferometry and thermography were compared. Using either holographic interferometry or thermography, relativelysmall-size defects in metal plates could be revealed. Holographic techniques have some limitations for industrial measurements. On the contrary, thermography has excellent prospects for on-line inspection, especially with scanning techniques.

Piirilevyn emissiivisyyden vakiointi lämpökamerasovelluksiin

Lämpökameroiden kehitys on mahdollistanut lämpökameroiden käytön myös erittäin pienien kohteiden tarkastelussa. Luotettava absoluuttisten lämpötilojen selvittäminen lämpökameralla vaatii, että tarkasteltavan kohteen emissiivisyys on kauttaaltaan vakio ja tunnettu. Käytännössä erilaisten materiaalipintojen emissiivisyyksissä on merkittäviä eroja, mikä aiheuttaa virheitä mittaustuloksiin. Tutkimuksen tavoitteena oli löytää halpa ja käytännöllinen keino piirilevyn emissiivisyyden vakiointiin. Työssä kartoitettiin erilaisia pinnoitteita, joille tehtiin resistanssi-, impedanssi- sekä lämpökameramittaukset. Mittauksilla selvitettiin pinnoitteen soveltuvuus emissiivisyyden vakiointiin. Lisäksi tutustuttiin pintapuolisesti pinnoiteaineiden kemialliseen rakenteeseen, jotta saatiin peruskäsitys siitä, onko aineiden kemiallisella rakenteella merkitystä pinnoiteaineen emissiivisyyden vakiointikykyyn. Tutkimustulosten perusteella tutkituista pinnoitteista parhaaksi todettiin talkkijauhe. Talkkipinnoitteella saatiin luotettavia mittaustuloksia. Tällä hetkellä pinnoitemenetelmää voidaan käyttää yksittäisten piirilevyjen testauksessa laboratorio-olosuhteissa. Tulevaisuudessa menetelmää voitaisiin soveltaa myös piirilevyjen tuotantolinjalle.

Visual Measurement and Modelling of Tool Wear in Rough Turning

Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

Automatic meter reading – benefits and applications

In liberalized electricity markets, which have taken place in many countries over the world, the electricity distribution companies operate in the competitive conditions. Therefore, accurate information about the customers’ energy consumption plays an essential role for the budget keeping of the distribution company and for correct planning and operation of the distribution network. This master’s thesis is focused on the description of the possible benefits for the electric utilities and residential customers from the automatic meter reading system usage. Major benefits of the AMR, illustrated in the thesis, are distribution network management, power quality monitoring, load modelling, and detection of the illegal usage of the electricity. By the example of the power system state estimation, it was illustrated that even the partial installation of the AMR in the customer side leads to more accurate data about the voltage and power levels in the whole network. The thesis also contains the description of the present situation of the AMR integration in Russia.

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.

Physical Realization of an Optical Automatic Target Recognition System

In the modern warfare there is an active development of a new trend connected with a robotic warfare. One of the critical elements of robotics warfare systems is an automatic target recognition system, allowing to recognize objects, based on the data received from sensors. This work considers aspects of optical realization of such a system by means of NIR target scanning at fixed wavelengths. An algorithm was designed, an experimental setup was built and samples of various modern gear and apparel materials were tested. For pattern testing the samples of actively arm engaged armies camouflages were chosen. Tests were performed both in clear atmosphere and in the artificial extremely humid and hot atmosphere to simulate field conditions.

Promoting Programming Learning. Engagement, Automatic Assessment with Immediate Feedback in Visualizations

The skill of programming is a key asset for every computer science student. Many studies have shown that this is a hard skill to learn and the outcomes of programming courses have often been substandard. Thus, a range of methods and tools have been developed to assist students’ learning processes. One of the biggest fields in computer science education is the use of visualizations as a learning aid and many visualization based tools have been developed to aid the learning process during last few decades. Studies conducted in this thesis focus on two different visualizationbased tools TRAKLA2 and ViLLE. This thesis includes results from multiple empirical studies about what kind of effects the introduction and usage of these tools have on students’ opinions and performance, and what kind of implications there are from a teacher’s point of view. The results from studies in this thesis show that students preferred to do web-based exercises, and felt that those exercises contributed to their learning. The usage of the tool motivated students to work harder during their course, which was shown in overall course performance and drop-out statistics. We have also shown that visualization-based tools can be used to enhance the learning process, and one of the key factors is the higher and active level of engagement (see. Engagement Taxonomy by Naps et al., 2002). The automatic grading accompanied with immediate feedback helps students to overcome obstacles during the learning process, and to grasp the key element in the learning task. These kinds of tools can help us to cope with the fact that many programming courses are overcrowded with limited teaching resources. These tools allows us to tackle this problem by utilizing automatic assessment in exercises that are most suitable to be done in the web (like tracing and simulation) since its supports students’ independent learning regardless of time and place. In summary, we can use our course’s resources more efficiently to increase the quality of the learning experience of the students and the teaching experience of the teacher, and even increase performance of the students. There are also methodological results from this thesis which contribute to developing insight into the conduct of empirical evaluations of new tools or techniques. When we evaluate a new tool, especially one accompanied with visualization, we need to give a proper introduction to it and to the graphical notation used by tool. The standard procedure should also include capturing the screen with audio to confirm that the participants of the experiment are doing what they are supposed to do. By taken such measures in the study of the learning impact of visualization support for learning, we can avoid drawing false conclusion from our experiments. As computer science educators, we face two important challenges. Firstly, we need to start to deliver the message in our own institution and all over the world about the new – scientifically proven – innovations in teaching like TRAKLA2 and ViLLE. Secondly, we have the relevant experience of conducting teaching related experiment, and thus we can support our colleagues to learn essential know-how of the research based improvement of their teaching. This change can transform academic teaching into publications and by utilizing this approach we can significantly increase the adoption of the new tools and techniques, and overall increase the knowledge of best-practices. In future, we need to combine our forces and tackle these universal and common problems together by creating multi-national and multiinstitutional research projects. We need to create a community and a platform in which we can share these best practices and at the same time conduct multi-national research projects easily.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

Utilization of Automatic Meter Reading in the Improvement of a District Heating System

A district heating system comprises production facilities, a distribution network, and heat consumers. The utilization of new energy metering and reading system (AMR) is increasing constantly in district heating systems. This heuristic study shows how the AMR system can be exploited in finding optimization opportunities in district heating system. In this study, the district heating system is mainly considered from the viewpoint of operational optimization. The focus is on the core processes, heat production and distribution. Three objectives were set to this study. The first one was to examine general optimization opportunities in district heating systems. Second, to figure out the benefits of AMR for general optimization opportunities. Finally, to define a methodology for process improvement endeavors. This study shows, through a case study, the usefulness of AMR in specifying current deficiencies in a district heating system. Based on a literature review, the methodology for the improvement of business processes is presented. Additionally, some issues related to future competitiveness of district heating are concerned. As a conclusion, some optimization objectives are considered more desirable than others. Study shows that AMR is useful in the specification of optimization targets in the district heating system. Further steps in optimization process were not examined in detail. That would seem to be interesting topic for further studies.