22 research outputs found
Cooperative Radio Communications for Green Smart Environments
The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin
Automatic lineament analysis techniques for remotely sensed imagery
Imperial Users onl
Texture and Colour in Image Analysis
Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews
Cooperative Radio Communications for Green Smart Environments
The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin
Mathematische morfologie in de beeldverwerking Mathematical Morphology in Image Processing
Het verwerken van een afbeelding met de computer laat ons toe de kwaliteit van dit beeld te verbeteren, specifieke objecten uit het beeld te segmenteren, of extra informatie tevoorschijn te halen. Mathematische morfologie is een set van wiskundige technieken uit de beeldverwerking die ons toelaat (de vormen in) beelden te analyseren. Dit proefschrift levert oplossingen voor een aantal problemen uit de beeldverwerking, met behulp van mathematische morfologie. Morfologie toepassen op zwart-wit- of grijswaardenbeelden is relatief eenvoudig, maar de theorie uitbreiden voor kleurbeelden stelt een aantal problemen. Aangezien een kleurbeeld veel meer nuttige informatie kan bevatten dan een grijswaardenbeeld, is zo'n uitbreiding wenselijk. We stellen het meerderheidsordeningsschema (MSS) voor, wat ons toelaat kleuren onderling te ordenen op een logische manier. Morfologische beeldverwerking met kleuren wordt dan mogelijk. Een ander onderzoek betreft polymeren en composieten. Deze materialen worden als glijlagers gebruikt in allerhande voorwerpen, zoals huishoudtoestellen, sluizen, poorten, etc. Vandaar dat de studie van de slijtage hiervan belangrijk is. We gaan na of het morfologische patroonspectrum, alsook vergelijkbare technieken, een bijdrage kan leveren aan het wrijvingsonderzoek van dergelijke materialen. Dit zou de snelheid en efficiëntie van de analyses kunnen verbeteren. We merken op dat de spectrale parameters interessante verbanden vertonen met de parameters van de proefopstelling. Het derde luik van de thesis betreft het ontwikkelen van een interpolatietechniek voor zwart-wit-beelden, gebaseerd op mathematische morfologie, genaamd mmINT. Interpolatie is nodig wanneer we wensen in te zoomen op een beeld of de resolutie van het beeld willen vergroten. Dit kan van pas komen wanneer we ingescande of gedownloade tekeningen van slechte kwaliteit (te lage resolutie) willen verbeteren. mmINT werkt aanzienlijk beter dan bestaande methodes. We ontwikkelden ook een snelle variant, mmINTone, en een uitbreiding voor grijswaardenbeelden, mmINTg
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Digital Image Processing via Combination of Low-Level and High-Level Approaches.
With the growth of computer power, Digital Image Processing plays a more
and more important role in the modern world, including the field of industry,
medical, communications, spaceflight technology etc. There is no clear
definition how to divide the digital image processing, but normally, digital
image processing includes three main steps: low-level, mid-level and highlevel
processing.
Low-level processing involves primitive operations, such as: image preprocessing
to reduce the noise, contrast enhancement, and image sharpening.
Mid-level processing on images involves tasks such as segmentation (partitioning
an image into regions or objects), description of those objects to
reduce them to a form suitable for computer processing, and classification
(recognition) of individual objects. Finally, higher-level processing involves
"making sense" of an ensemble of recognised objects, as in image analysis.
Based on the theory just described in the last paragraph, this thesis is
organised in three parts: Colour Edge and Face Detection; Hand motion
detection; Hand Gesture Detection and Medical Image Processing.
II
In Colour Edge Detection, two new images G-image and R-image are
built through colour space transform, after that, the two edges extracted
from G-image and R-image respectively are combined to obtain the final
new edge. In Face Detection, a skin model is built first, then the boundary
condition of this skin model can be extracted to cover almost all of the skin
pixels. After skin detection, the knowledge about size, size ratio, locations
of ears and mouth is used to recognise the face in the skin regions.
In Hand Motion Detection, frame differe is compared with an automatically
chosen threshold in order to identify the moving object. For some special
situations, with slow or smooth object motion, the background modelling
and frame differencing are combined in order to improve the performance.
In Hand Gesture Recognition, 3 features of every testing image are input
to Gaussian Mixture Model (GMM), and then the Expectation Maximization
algorithm (EM)is used to compare the GMM from testing images and GMM
from training images in order to classify the results.
In Medical Image Processing (mammograms), the Artificial Neural Network
(ANN) and clustering rule are applied to choose the feature. Two
classifier, ANN and Support Vector Machine (SVM), have been applied to
classify the results, in this processing, the balance learning theory and optimized
decision has been developed are applied to improve the performance