Mechatronic solutions for measuring disturbance levels within a cochlea

Hearing implants are an important devices for combating deafness over the next 15 years. In this paper, we focus on the means to determine the sensitivity of the hearing organ to disturbances produced by implants and other interventions, and those induced by implantation. The preservation of residual hearing is an important aspect to be considered, however, the sensitivity of this to the process of implantation, device location and power levels is not well understood. Within this paper, a new experimental set-up to contrast the merits of different implantation techniques, implant location and power transmission are discussed and the initial results regarding disturbance levels using different surgical techniques are described.

On covariate factor detection and removal for robust gait recognition

We propose a novel bolt-on module capable of boosting the robustness of various single compact 2D gait representations. Gait recognition is negatively influenced by covariate factors including clothing and time which alter the natural gait appearance and motion. Contrary to traditional gait recognition, our bolt-on module remedies this by a dedicated covariate factor detection and removal procedure which we quantitatively and qualitatively evaluate. The fundamental concept of the bolt-on module is founded on exploiting the pixel-wise composition of covariate factors. Results demonstrate how our bolt-on module is a powerful component leading to significant improvements across gait representations and datasets yielding state-of-the-art results.

Multi-scale colorectal tumour segmentation using a novel coarse to fine strategy

This paper addresses the problem of colorectal tumour segmentation in complex real world imagery. For efficient segmentation, a multi-scale strategy is developed for extracting the potentially cancerous region of interest (ROI) based on colour histograms while searching for the best texture resolution. To achieve better segmentation accuracy, we apply a novel bag-of-visual-words method based on rotation invariant raw statistical features and random projection based l2-norm sparse representation to classify tumour areas in histopathology images. Experimental results on 20 real world digital slides demonstrate that the proposed algorithm results in better recognition accuracy than several state of the art segmentation techniques.

Abnormal Pedestrian Trajectory analysis based on arbitrary-length clustering

This papers examines the use of trajectory distance measures and clustering techniques to define normal
and abnormal trajectories in the context of pedestrian tracking in public spaces. In order to detect abnormal
trajectories, what is meant by a normal trajectory in a given scene is firstly defined. Then every trajectory
that deviates from this normality is classified as abnormal. By combining Dynamic Time Warping and a
modified K-Means algorithms for arbitrary-length data series, we have developed an algorithm for trajectory
clustering and abnormality detection. The final system performs with an overall accuracy of 83% and 75%
when tested in two different standard datasets.

Development of N N SMRT for N a power of 2 and its Applications in Image Enhancement

Digital Image Processing is a rapidly evolving eld with growing applications in Science and Engineering. It involves changing the nature of an image in order to either improve its pictorial information for human interpretation or render it more suitable for autonomous machine perception. One of the major areas of image processing for human vision applications is image enhancement. The principal goal of image enhancement is to improve visual quality of an image, typically by taking advantage of the response of human visual system. Image enhancement methods are carried out usually in the pixel domain. Transform domain methods can often provide another way to interpret and understand image contents. A suitable transform, thus selected, should have less computational complexity. Sequency ordered arrangement of unique MRT (Mapped Real Transform) coe cients can give rise to an integer-to-integer transform, named Sequency based unique MRT (SMRT), suitable for image processing applications. The development of the SMRT from UMRT (Unique MRT), forward & inverse SMRT algorithms and the basis functions are introduced. A few properties of the SMRT are explored and its scope in lossless text compression is presented.

Panossyöttökasvatusprosessin automatisointi

Tutkimuskäyttöön tarkoitettujen rekombinanttiproteiinien tuottaminen fermentoimalla on yleinen menetelmä bioteollisuudessa. Mikrobit kasvatetaan fermentorissa, joka tarjoaa kontrolloidun kasvuympäristön ja sopivat tuotto-olosuhteet halutulle tuotteelle. Eräs fermentointimuodoista on korkeatuottoinen ja pitkäkestoinen panossyöttökasvatus, jossa saavutetaan panoskavatusta merkittävästi korkeampi solutiheys jatkamalla panosvaiheen jälkeen kasvua rajoittavan substraatin syöttöä. Laboratoriomittakaavassa fermentorikasvatusten tilavuudet vaihtelevat litrasta kymmeniin ja niissä kasvatusta seurataan sekä ohjataan joko fermentorista tai tietokoneesta. Tyypillisessä fermentointiprosessissa operaattori tarkkailee muun muassa vaahdonkorkeutta sekä käynnistää pumppuja olosuhteiden muuttuessa. Tällaiset tehtävät ovat teollisen mittakaavan laitteistoissa usein automatisoituja. Diplomityön tarkoituksena oli päivittää kahden Turun yliopiston biotekniikan laboratoriossa sijaitsevan BioFlo® -sarjan pöytäfermentorin MS-DOS -pohjainen tietokoneohjausohjelma nykyaikaiseksi ja lisätä siihen etäseuranta ja -ohjaus. Ohjelmaan oli tarkoitus liittää erillinen optinen solutiheysanturi, jonka lukemien häiriötä haluttiin myös vähentää signaalinkäsittelyllä. Lisäksi vaahdonestoaineen ja indusorin lisäykset haluttiin automatisoida panossyöttökasvatuksessa. Vaahdonkorkeuden havaitsemisen mahdollisuutta konenäön menetelmin haluttiin selvittää, jotta vaahdonestoaineen automaattiset lisäykset voitaisiin toteuttaa nettikameran syötteen perusteella. Koekasvatuksilla osoitettiin päivitetyn ohjausohjelman toimivan panos- ja panossyöttömuodoilla. Uuden käyttöliittymän avulla pystyttiin automatisoimaan panoskasvatuksen lisäykset ja syöttönopeuden muutokset sekä tunnistamaan kasvatusliuosten vaahdonkorkeutta vaahdonestoaineen lisäykseen riittävällä kahden senttimetrin tarkkuudella. Lisäksi käyttöliittymä mahdollisti kasvatuksen ohjauksen ja seurauksen myös etänä. Työssä kehitetty ohjausohjelma julkaistiin avoimena ohjelmana ilman etä- ja nettikameratoimintoja. Ohjelma toimii hyvin BioFlo® -sarjan fermentorien käyttöliittymänä, mutta avoimen lähdekoodin ansiosta kuka tahansa voi hyödyntää ohjelmaa pohjana myös uusissa projekteissa tai muissa fermentorimalleissa.

Hand gesture recognition system based in computer vision and machine learning : applications on human-machine interaction

Sendo uma forma natural de interação homem-máquina, o reconhecimento de gestos implica uma forte componente de investigação em áreas como a visão por computador e a aprendizagem computacional. O reconhecimento gestual é uma área com aplicações muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utilização de dispositivos extras. Assim, o objectivo principal da investigação na área de reconhecimento de gestos aplicada à interacção homemmáquina é o da criação de sistemas, que possam identificar gestos específicos e usálos para transmitir informações ou para controlar dispositivos. Para isso as interfaces baseados em visão para o reconhecimento de gestos, necessitam de detectar a mão de forma rápida e robusta e de serem capazes de efetuar o reconhecimento de gestos em tempo real. Hoje em dia, os sistemas de reconhecimento de gestos baseados em visão são capazes de trabalhar com soluções específicas, construídos para resolver um determinado problema e configurados para trabalhar de uma forma particular. Este projeto de investigação estudou e implementou soluções, suficientemente genéricas, com o recurso a algoritmos de aprendizagem computacional, permitindo a sua aplicação num conjunto alargado de sistemas de interface homem-máquina, para reconhecimento de gestos em tempo real. A solução proposta, Gesture Learning Module Architecture (GeLMA), permite de forma simples definir um conjunto de comandos que pode ser baseado em gestos estáticos e dinâmicos e que pode ser facilmente integrado e configurado para ser utilizado numa série de aplicações. É um sistema de baixo custo e fácil de treinar e usar, e uma vez que é construído unicamente com bibliotecas de código. As experiências realizadas permitiram mostrar que o sistema atingiu uma precisão de 99,2% em termos de reconhecimento de gestos estáticos e uma precisão média de 93,7% em termos de reconhecimento de gestos dinâmicos. Para validar a solução proposta, foram implementados dois sistemas completos. O primeiro é um sistema em tempo real capaz de ajudar um árbitro a arbitrar um jogo de futebol robótico. A solução proposta combina um sistema de reconhecimento de gestos baseada em visão com a definição de uma linguagem formal, o CommLang Referee, à qual demos a designação de Referee Command Language Interface System (ReCLIS). O sistema identifica os comandos baseados num conjunto de gestos estáticos e dinâmicos executados pelo árbitro, sendo este posteriormente enviado para um interface de computador que transmite a respectiva informação para os robôs. O segundo é um sistema em tempo real capaz de interpretar um subconjunto da Linguagem Gestual Portuguesa. As experiências demonstraram que o sistema foi capaz de reconhecer as vogais em tempo real de forma fiável. Embora a solução implementada apenas tenha sido treinada para reconhecer as cinco vogais, o sistema é facilmente extensível para reconhecer o resto do alfabeto. As experiências também permitiram mostrar que a base dos sistemas de interação baseados em visão pode ser a mesma para todas as aplicações e, deste modo facilitar a sua implementação. A solução proposta tem ainda a vantagem de ser suficientemente genérica e uma base sólida para o desenvolvimento de sistemas baseados em reconhecimento gestual que podem ser facilmente integrados com qualquer aplicação de interface homem-máquina. A linguagem formal de definição da interface pode ser redefinida e o sistema pode ser facilmente configurado e treinado com um conjunto de gestos diferentes de forma a serem integrados na solução final.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Blood type classification using computer vision and machine learning

In emergency situations, where time for blood transfusion is reduced, the O negative blood type (the universal donor) is administrated. However, sometimes even the universal donor can cause transfusion reactions that can be fatal to the patient. As commercial systems do not allow fast results and are not suitable for emergency situations, this paper presents the steps considered for the development and validation of a prototype, able to determine blood type compatibilities, even in emergency situations. Thus it is possible, using the developed system, to administer a compatible blood type, since the first blood unit transfused. In order to increase the system’s reliability, this prototype uses different approaches to classify blood types, the first of which is based on Decision Trees and the second one based on support vector machines. The features used to evaluate these classifiers are the standard deviation values, histogram, Histogram of Oriented Gradients and fast Fourier transform, computed on different regions of interest. The main characteristics of the presented prototype are small size, lightweight, easy transportation, ease of use, fast results, high reliability and low cost. These features are perfectly suited for emergency scenarios, where the prototype is expected to be used.

The human eye as human-machine interface

Eye tracking as an interface to operate a computer is under research for a while and new systems are still being developed nowadays that provide some encouragement to those bound to illnesses that incapacitates them to use any other form of interaction with a computer. Although using computer vision processing and a camera, these systems are usually based on head mount technology being considered a contact type system. This paper describes the implementation of a human-computer interface based on a fully non-contact eye tracking vision system in order to allow people with tetraplegia to interface with a computer. As an assistive technology, a graphical user interface with special features was developed including a virtual keyboard to allow user communication, fast access to pre-stored phrases and multimedia and even internet browsing. This system was developed with the focus on low cost, user friendly functionality and user independency and autonomy.