Efficient Architecture and Implementation of Vector Median Filter in Co-Design Context

This work presents an efficient fast parallel architecture of the Vector Median Filter (VMF) using combined hardware/software (HW/SW) implementation. The hardware part of the system is implemented using VHDL language, whereas the software part is developed using C/C++ language. The software part of the embedded system uses the NIOS-II softcore processor and the operating system used is μClinux. The comparison between the software and HW/SW solutions shows that adding a hardware part in the design attempts to speed up the filtering process compared to the software solution. This efficient embedded system implementation can perform well in several image processing applications

NONLINEAR OPERATORS FOR IMAGE PROCESSING: DESIGN, IMPLEMENTATION AND MODELING TECHNIQUES FOR POWER ESTIMATION

1998/1999Negli ultimi anni passati le applicazioni multimediali hanno visto uno sviluppo notevole, trovando applicazione in un gran numero di campi. Applicazioni come video conferenze, diagnostica medica, telefonia mobile e applicazioni militari necessitano il trattamento di una gran mole di dati ad alta velocità. Pertanto, l'elaborazione di immagini e di dati vocali è molto importante ed è stata oggetto di numerosi sforzi, nel tentativo di trovare algoritmi sempre più veloci ed efficaci. Tra gli algoritmi proposti, noi crediamo che gli operatori razionali svolgano un ruolo molto importante, grazie alla loro versatilità ed efficacia nell'elaborazione di dati. Negli ultimi anni sono stati proposti diversi algoritmi, dimostrando che questi operatori possono essere molto vantaggiosi in diverse applicazioni, producendo buoni risultati. Lo scopo di questo lavoro è di realizzare alcuni di questi algoritmi e, quindi, dimostrare che i filtri razionali, in particolare, possono essere realizzati senza ricorrere a sistemi di grandi dimensioni e possono raggiungere frequenze operative molto alte. Una volta che il blocco fondamentale di un sistema basato su operatori razionali sia stato realizzato, esso pu6 essere riusato con successo in molte altre applicazioni. Dal punto di vista del progettista, è importante avere uno schema generale di studio, che lo renda capace di studiare le varie configurazioni del sistema da realizzare e di analizzare i compromessi tra le variabili di progetto. In particolare, per soddisfare l'esigenza di metodi versatili per la stima della potenza, abbiamo sviluppato una tecnica di macro modellizazione che permette al progettista di stimare velocemente ed accuratamente la potenza dissipata da un circuito. La tesi è organizzata come segue: Nel Capitolo 1 alcuni sono presentati alcuni algoritmi studiati per la realizzazione. Ne viene data solo una veloce descrizione, lasciando comunque al lettore interessato dei riferimenti bibliografici. Nel Capitolo 2 vengono discusse le architetture fondamentali usate per la realizzazione. Principalmente sono state usate architetture a pipeline, ma viene data anche una descrizione degli approcci oggigiorno disponibili per l'ottimizzazione delle temporizzazioni. Nel Capitolo 3 sono presentate le realizzazioni di due sistemi studiati per questa tesi. Gli approcci seguiti si basano su ASIC e FPGA. Richiedono tecniche e soluzioni diverse per il progetto del sistema, per cui é interessante vedere cosa pu6 essere fatto nei due casi. Infine, nel Capitolo 4, descriviamo la nostra tecnica di macro modellizazione per la stima di potenza, dando una breve visione delle tecniche finora proposte e facendo vedere quali sono i vantaggi che il nostro metodo comporta per il progetto.In the past few years, multimedia application have been growing very fast, being applied to a large variety of fields. Applications like video conference, medical diagnostic, mobile phones, military applications require to handle large amount of data at high rate. Images as well as voice data processing are therefore very important and they have been subjected to a lot of efforts in order to find always faster and effective algorithms. Among image processing algorithms, we believe that rational operators assume an important role, due to their versatility and effectiveness in data processing. In the last years, several algorithms have been proposed, demonstrating that these operators can be very suitable in different applications with very good results. The aim of this work is to implement some of these algorithm and, therefore, demonstrate that rational filters, in particular, can be implemented without requiring large sized systems and they can operate at very high frequencies. Once the basic building block of a rational based system has been implemented, it can be successfully reused in many other applications. From the designer point of view, it is important to have a general framework, which makes it able to study various configurations of the system to be implemented and analyse the trade-off among the design variables. In particular, to meet the need far versatile tools far power estimation, we developed a new macro modelling technique, which allows the designer to estimate the power dissipated by a circuit quickly and accurately. The thesis is organized as follows: In chapter 1 we present some of the algorithms which have been studied for implementation. Only a brief overview is given, leaving to the interested reader some references in literature. In chapter 2 we discuss the basic architectures used for the implementations. Pipelined structures have been mainly used for this thesis, but an overview of the nowaday available approaches for timing optimization is presented. In chapter 3 we present two of the implementation designed for this thesis. The approaches followed are ASIC driven and FPGA drive. They require different techniques and different solution for the design of the system, therefore it is interesting to see what can be done in both the cases. Finally, in chapter 4, we describe our macro modelling techniques for power estimation, giving a brief overview of the up to now proposed techniques and showing the advantages our method brings to the design.XII Ciclo1969Versione digitalizzata della tesi di dottorato cartacea

Microarray image processing: A novel neural network framework

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Due to the vast success of bioengineering techniques, a series of large-scale analysis tools has been developed to discover the functional organization of cells. Among them, cDNA microarray has emerged as a powerful technology that enables biologists to cDNA microarray technology has enabled biologists to study thousands of genes simultaneously within an entire organism, and thus obtain a better understanding of the gene interaction and regulation mechanisms involved. Although microarray technology has been developed so as to offer high tolerances, there exists high signal irregularity through the surface of the microarray image. The imperfection in the microarray image generation process causes noises of many types, which contaminate the resulting image. These errors and noises will propagate down through, and can significantly affect, all subsequent processing and analysis. Therefore, to realize the potential of such technology it is crucial to obtain high quality image data that would indeed reflect the underlying biology in the samples. One of the key steps in extracting information from a microarray image is segmentation: identifying which pixels within an image represent which gene. This area of spotted microarray image analysis has received relatively little attention relative to the advances in proceeding analysis stages. But, the lack of advanced image analysis, including the segmentation, results in sub-optimal data being used in all downstream analysis methods. Although there is recently much research on microarray image analysis with many methods have been proposed, some methods produce better results than others. In general, the most effective approaches require considerable run time (processing) power to process an entire image. Furthermore, there has been little progress on developing sufficiently fast yet efficient and effective algorithms the segmentation of the microarray image by using a highly sophisticated framework such as Cellular Neural Networks (CNNs). It is, therefore, the aim of this thesis to investigate and develop novel methods processing microarray images. The goal is to produce results that outperform the currently available approaches in terms of PSNR, k-means and ICC measurements.Aleppo University, Syri

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world

NASA JSC neural network survey results

A survey of Artificial Neural Systems in support of NASA's (Johnson Space Center) Automatic Perception for Mission Planning and Flight Control Research Program was conducted. Several of the world's leading researchers contributed papers containing their most recent results on artificial neural systems. These papers were broken into categories and descriptive accounts of the results make up a large part of this report. Also included is material on sources of information on artificial neural systems such as books, technical reports, software tools, etc

Deep Learning Methods for Industry and Healthcare

L'abstract è presente nell'allegato / the abstract is in the attachmen

Measurements, Models, Systems and Design

531 s.

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide

EIT Reconstruction Algorithms: Pitfalls, Challenges and Recent Developments

We review developments, issues and challenges in Electrical Impedance Tomography (EIT), for the 4th Workshop on Biomedical Applications of EIT, Manchester 2003. We focus on the necessity for three dimensional data collection and reconstruction, efficient solution of the forward problem and present and future reconstruction algorithms. We also suggest common pitfalls or ``inverse crimes'' to avoid.Comment: A review paper for the 4th Workshop on Biomedical Applications of EIT, Manchester, UK, 200