Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Proceedings of the EAA Joint Symposium on Auralization and Ambisonics 2014

In consideration of the remarkable intensity of research in the field of Virtual Acoustics, including different areas such as sound field analysis and synthesis, spatial audio technologies, and room acoustical modeling and auralization, it seemed about time to organize a second international symposium following the model of the first EAA Auralization Symposium initiated in 2009 by the acoustics group of the former Helsinki University of Technology (now Aalto University). Additionally, research communities which are focused on different approaches to sound field synthesis such as Ambisonics or Wave Field Synthesis have, in the meantime, moved closer together by using increasingly consistent theoretical frameworks. Finally, the quality of virtual acoustic environments is often considered as a result of all processing stages mentioned above, increasing the need for discussions on consistent strategies for evaluation. Thus, it seemed appropriate to integrate two of the most relevant communities, i.e. to combine the 2nd International Auralization Symposium with the 5th International Symposium on Ambisonics and Spherical Acoustics. The Symposia on Ambisonics, initiated in 2009 by the Institute of Electronic Music and Acoustics of the University of Music and Performing Arts in Graz, were traditionally dedicated to problems of spherical sound field analysis and re-synthesis, strategies for the exchange of ambisonics-encoded audio material, and – more than other conferences in this area – the artistic application of spatial audio systems. This publication contains the official conference proceedings. It includes 29 manuscripts which have passed a 3-stage peer-review with a board of about 70 international reviewers involved in the process. Each contribution has already been published individually with a unique DOI on the DepositOnce digital repository of TU Berlin. Some conference contributions have been recommended for resubmission to Acta Acustica united with Acustica, to possibly appear in a Special Issue on Virtual Acoustics in late 2014. These are not published in this collection.European Acoustics Associatio

Wavelets and Subband Coding

First published in 1995, Wavelets and Subband Coding offered a unified view of the exciting field of wavelets and their discrete-time cousins, filter banks, or subband coding. The book developed the theory in both continuous and discrete time, and presented important applications. During the past decade, it filled a useful need in explaining a new view of signal processing based on flexible time-frequency analysis and its applications. Since 2007, the authors now retain the copyright and allow open access to the book

Advanced Biometrics with Deep Learning

Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others

Image Stitching

Projecte final de carrera fet en col.laboració amb University of Limerick. Department of Electronic and Computer EngineeringEnglish: Image processing is any form of signal processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or, a set of characteristics or parameters related to the image. Most image processing techniques involve treating the image as a two-dimensional signal and applying standard signal processing techniques to it. Specifically, image stitching presents different stages to render two or more overlapping images into a seamless stitched image, from the detection of features to blending in a final image. In this process, Scale Invariant Feature Transform (SIFT) algorithm can be applied to perform the detection and matching control points step, due to its good properties. The process of create an automatic and effective whole stitching process leads to analyze different methods of the stitching stages. Several commercial and online software tools are available to perform the stitching process, offering diverse options in different situations. This analysis involves the creation of a script to deal with images and project data files. Once the whole script is generated, the stitching process is able to achieve an automatic execution allowing good quality results in the final composite image.Castellano: Procesado de imagen es cualquier tipo de procesado de señal en aquel que la entrada es una imagen, como una fotografía o fotograma de video; la salida puede ser una imagen o conjunto de características y parámetros relacionados con la imagen. Muchas de las técnicas de procesado de imagen implican un tratamiento de la imagen como señal en dos dimensiones, y para ello se aplican técnicas estándar de procesado de señal. Concretamente, la costura o unión de imágenes presenta diferentes etapas para unir dos o más imágenes superpuestas en una imagen perfecta sin costuras, desde la detección de puntos clave en las imágenes hasta su mezcla en la imagen final. En este proceso, el algoritmo Scale Invariant Feature Transform (SIFT) puede ser aplicado para desarrollar la fase de detección y selección de correspondencias entre imágenes debido a sus buenas cualidades. El desarrollo de la creación de un completo proceso de costura automático y efectivo, pasa por analizar diferentes métodos de las etapas del cosido de las imágenes. Varios software comerciales y gratuitos son capaces de llevar a cabo el proceso de costura, ofreciendo diferentes alternativas en distintas situaciones. Este análisis implica la creación de una secuencia de comandos que trabaja con las imágenes y con archivos de datos del proyecto generado. Una vez esta secuencia es creada, el proceso de cosido de imágenes es capaz de lograr una ejecución automática permitiendo unos resultados de calidad en la imagen final.Català: Processament d'imatge és qualsevol tipus de processat de senyal en aquell que l'entrada és una imatge, com una fotografia o fotograma de vídeo, i la sortida pot ser una imatge o conjunt de característiques i paràmetres relacionats amb la imatge. Moltes de les tècniques de processat d'imatge impliquen un tractament de la imatge com a senyal en dues dimensions, i per això s'apliquen tècniques estàndard de processament de senyal. Concretament, la costura o unió d'imatges presenta diferents etapes per unir dues o més imatges superposades en una imatge perfecta sense costures, des de la detecció de punts clau en les imatges fins a la seva barreja en la imatge final. En aquest procés, l'algoritme Scale Invariant Feature Transform (SIFT) pot ser aplicat per desenvolupar la fase de detecció i selecció de correspondències entre imatges a causa de les seves bones qualitats. El desenvolupament de la creació d'un complet procés de costura automàtic i efectiu, passa per analitzar diferents mètodes de les etapes del cosit de les imatges. Diversos programari comercials i gratuïts són capaços de dur a terme el procés de costura, oferint diferents alternatives en diverses situacions. Aquesta anàlisi implica la creació d'una seqüència de commandes que treballa amb les imatges i amb arxius de dades del projecte generat. Un cop aquesta seqüència és creada, el procés de cosit d'imatges és capaç d'aconseguir una execució automàtica permetent uns resultats de qualitat en la imatge final

High Performance Geospatial Analysis on Emerging Parallel Architectures

Geographic information systems (GIS) are performing increasingly sophisticated analyses on growing data sets. These analyses demand high performance. At the same time, modern computing platforms increasingly derive their performance from several forms of parallelism. This dissertation explores the available parallelism in several GIS-applied algorithms: viewshed calculation, image feature transform, and feature analysis. It presents implementations of these algorithms that exploit parallel processing to reduce execution time, and analyzes the effectiveness of the implementations in their use of parallel processing

Proceedings of the EAA Spatial Audio Signal Processing symposium: SASP 2019

International audienc