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.

Exploration and Design of Power-Efficient Networked Many-Core Systems

Multiprocessing is a promising solution to meet the requirements of near future applications. To get full benefit from parallel processing, a manycore system needs efficient, on-chip communication architecture. Networkon- Chip (NoC) is a general purpose communication concept that offers highthroughput, reduced power consumption, and keeps complexity in check by a regular composition of basic building blocks. This thesis presents power efficient communication approaches for networked many-core systems. We address a range of issues being important for designing power-efficient manycore systems at two different levels: the network-level and the router-level. From the network-level point of view, exploiting state-of-the-art concepts such as Globally Asynchronous Locally Synchronous (GALS), Voltage/ Frequency Island (VFI), and 3D Networks-on-Chip approaches may be a solution to the excessive power consumption demanded by today’s and future many-core systems. To this end, a low-cost 3D NoC architecture, based on high-speed GALS-based vertical channels, is proposed to mitigate high peak temperatures, power densities, and area footprints of vertical interconnects in 3D ICs. To further exploit the beneficial feature of a negligible inter-layer distance of 3D ICs, we propose a novel hybridization scheme for inter-layer communication. In addition, an efficient adaptive routing algorithm is presented which enables congestion-aware and reliable communication for the hybridized NoC architecture. An integrated monitoring and management platform on top of this architecture is also developed in order to implement more scalable power optimization techniques. From the router-level perspective, four design styles for implementing power-efficient reconfigurable interfaces in VFI-based NoC systems are proposed. To enhance the utilization of virtual channel buffers and to manage their power consumption, a partial virtual channel sharing method for NoC routers is devised and implemented. Extensive experiments with synthetic and real benchmarks show significant power savings and mitigated hotspots with similar performance compared to latest NoC architectures. The thesis concludes that careful codesigned elements from different network levels enable considerable power savings for many-core systems.

Video transcoding in a distributed cloud computing environment

Video transcoding refers to the process of converting a digital video from one format into another format. It is a compute-intensive operation. Therefore, transcoding of a large number of simultaneous video streams requires a large amount of computing resources. Moreover, to handle di erent load conditions in a cost-e cient manner, the video transcoding service should be dynamically scalable. Infrastructure as a Service Clouds currently offer computing resources, such as virtual machines, under the pay-per-use business model. Thus the IaaS Clouds can be leveraged to provide a coste cient, dynamically scalable video transcoding service. To use computing resources e ciently in a cloud computing environment, cost-e cient virtual machine provisioning is required to avoid overutilization and under-utilization of virtual machines. This thesis presents proactive virtual machine resource allocation and de-allocation algorithms for video transcoding in cloud computing. Since users' requests for videos may change at di erent times, a check is required to see if the current computing resources are adequate for the video requests. Therefore, the work on admission control is also provided. In addition to admission control, temporal resolution reduction is used to avoid jitters in a video. Furthermore, in a cloud computing environment such as Amazon EC2, the computing resources are more expensive as compared with the storage resources. Therefore, to avoid repetition of transcoding operations, a transcoded video needs to be stored for a certain time. To store all videos for the same amount of time is also not cost-e cient because popular transcoded videos have high access rate while unpopular transcoded videos are rarely accessed. This thesis provides a cost-e cient computation and storage trade-o strategy, which stores videos in the video repository as long as it is cost-e cient to store them. This thesis also proposes video segmentation strategies for bit rate reduction and spatial resolution reduction video transcoding. The evaluation of proposed strategies is performed using a message passing interface based video transcoder, which uses a coarse-grain parallel processing approach where video is segmented at group of pictures level.

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.

Big Data Processing in the Cloud: a Hydra/Sufia Experience

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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

Effects of feed processing on the apparent ileal digestibility of amino acids in pig diets containing wheat bran or wheat middlings

Selostus: Prosessoinnin vaikutus vehnän sivutuotteita sisältävien rehuseosten aminohappojen ohutsuolisulavuuteen sioilla

Stress intensity factor of wood from crack-tip displacement fields obtained from digital image processing

Abstract

International comparison of Russian food processing industry -Finnish perspective

Työn päätavoitteena on kartoittaa Venäjän elintarviketeollisuutta ulkomaisen investoijan näkökulmasta. Tutkimus arvioi liiketoimintamahdollisuuksia ja kilpailutilannetta Venäjän elintarviketeollisuudessa ja auttaa ulkomaisia yrityksiä toteuttamaan liiketoimintastrategioitaan Venäjällä. Venäjän ja muiden siirtymätalousmaiden markkinatilannevertailujen lisäksi Venäjän alueita verrataan keskenään. Myös mahdollisen WTO jäsenyyden vaikutuksia arvioidaan. Kommunismin perintö vaikuttaa edelleen Venäjän elintarviketeollisuuteen ja maatalouteen. Maatalouden tuottavuus on kaukana länsimaisesta tasosta ja maatiloilta puuttuu rahoitusta. Etenkin maidon- ja lihanjalostajat kärsivät raaka-ainepulasta. Venäjän kriisi vuonna 1998 vahvisti paikallista teollisuustuotantoa mutta aiheutti ongelmia ulkomaisille investoijille ja yrityksille, jotka vievät tuotteitaan Venäjälle. Edut, joita mahdollinen maailmankauppajärjestö WTO:n jäsenyys tuo, ovat merkittävämpiä Venäjälle kuin sen kauppakumppaneille. Venäjän alueet eivät ole yhtäläisesti kehittyneitä ja kuluttajien ostovoima vaihtelee paljon. Itsestään selvin ja houkuttelevin vaihtoehto menestyvien elintarvikeyritysten laajentumiselle löytyy alueilta, joilla ostovoima on suurin. Tähän asti kansainväliset elintarvikeyritykset ovat olleet enemmän kiinnostuneita Itä- ja Keski-Euroopan maista. Käytettävissä olevat tulot ovat Itä- ja Keski-Euroopan maissa suurempia kuin Venäjällä, joten tuottajat pystyvät myymään myös kalliimpia tuotteita. Työvoimakustannukset Venäjällä tulevat olemaan suotuisia vielä muutaman vuosikymmenen ja markkinoiden koko on merkittävä. Siksi kansainvälisillä elintarvikeyrityksillä riittää kiinnostusta tulevaisuudessa investoida myös Venäjälle.

Cutting of Frozen Wood

The objective of this master's thesis was to develop a system for measuring the cutting forces of frozen wood. In northern parts of the world cuttingof frozen wood is one of the major problem. During winter and early spring the temperature inside the wood cells will fall below Zero degrees that strongly influences on the properties of the wood. These variations of properties will effects on the blade nomenclature while cutting the frozen wood. However the end results will cause uneven cutting forces. Cutting forces, Chip formation, wearing of the blade and the quality of the machined surface are difficult task. In this project we are attempting to find the variation of cutting forces and properties of frozen wood at four different temperatures (-20 , -10, 0 and + 10 degrees). The linear planning machine was used for measuring the cuttingforces. The cutting was done parallel to the long axis of wood due to the nature of pine wood and the structure of the plane. A considerable amount of work andtime was used for collecting and processing the numerical information from the sensors of the measuring system. There were some alterations suggested to the construction of the plane and the sensor system.

A Feasibility Study of a Pelleting Plant as an Option for By Product Upgrading in Wood-Processing Industry

Tämän kannattavuustutkimuksen lähtökohtana oli se, että Yhtyneet Sahat Oy:n Kaukaan sahalla ja Luumäen jatkojalostuslaitoksella haluttiin selvittää pellettitehtaan kannattavuus nykyisessä markkinatilanteessa. Tämä työon luonteeltaan teknis-taloudellinen selvitys eli ns. feasibility study. Pelletöintiprosessi on tekniikaltaan yksinkertainen eikä edellytä korkea teknologian laitteita. Toimiala on maailmanlaajuisesti varsin uusi. Suomessa pellettimarkkinat ovat vielä pienet ja kehittymättömät, mutta kasvua on viime vuosina tapahtunut. Valtaosa kotimaan tuotannosta menee vientiin. Investoinnin laskentaprosessissa saadut tuotannon alkuarvot sekä kustannusrakenteen määrittelyt ovat perustana varsinaisille kannattavuuslaskelmille. Laskelmista on selvitetty investointeihin liittyvät yleisimmät taloudelliset tunnusluvut ja herkimpiä muuttujia on tutkittu ja pohdittu herkkyysanalyysiä apuna käyttäen.