Special Issue "Advances in Applied Signal and Image Processing Technology"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 10 February 2022.

Special Issue Editors

Dr. Samuel Morillas
E-Mail Website
Guest Editor
Departamento de Matemática Aplicada, Universitat Politècnica de València, 46022 Valencia, Spain
Interests: fuzzy logic; image processing; vision science; perceptual imaging
Dr. Pedro Latorre-Carmona
E-Mail Website
Guest Editor
Department of Computer Engineering, University of Burgos, Avda Cantabria s/n, 09006 Burgos, Spain
Interests: multispectral; colour and grey scale image processing; colorimetry; vision physics; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Dr. Nuria Ortigosa
E-Mail Website
Guest Editor
Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, 46022 Valencia, Spain
Interests: biomedical signal processing; computer vision; bioengineering; functional analysis; fuzzy logic; artificial intelligence

Special Issue Information

Dear Colleagues,

Signals and images are ubiquitous nowadays as they are present in many daily situations, ranging from consumer and health applications to industrial process monitoring and surveillance. Developments in the signal and image processing fields allow us to model and process signals and images using a series of frameworks and paradigms, such as vector manifolds, Fourier analysis, cosine and wavelet transforms, time–frequency analysis,  differential equations, statistical models, fuzzy logic and machine learning. Nevertheless, the development of new processing methods, usually designed and optimized for particular applications, and the development of the latter is an ongoing process. This Special Issue is devoted to the publication of new, scientifically sound, signal and image processing methods and applications of them. Contributions from both theoretical advances and applications are welcome. The scope of the Special Issue includes, but is not limited to, the following topics:

  • Health-related applications of signals and images;
  • E-health image/signal-based applications;
  • Biomedical signal and image processing;
  • Machine learning based methods for signals and images;
  • Perceptual imaging;
  • Vision Science;
  • Computer Vision;
  • New applications of color imaging;
  • Image quality measures;
  • Image and signal compression and transmission methods;
  • New image synthesis methods;
  • Artificial intelligence applications on image and signal processing;
  • Image retrieval;
  • Video surveillance;
  • Other new signal and image processing methods and applications.

Dr. Samuel Morillas
Dr. Pedro Latorre-Carmona
Dr. Nuria Ortigosa
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2300 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • signal processing
  • image processing
  • applications

Published Papers (1 paper)

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Research

Article
Experimental Assessment of Feature Extraction Techniques Applied to the Identification of Properties of Common Objects, Using a Radar System
Appl. Sci. 2021, 11(15), 6745; https://doi.org/10.3390/app11156745 - 22 Jul 2021
Viewed by 539
Abstract
Radar technology has evolved considerably in the last few decades. There are many areas where radar systems are applied, including air traffic control in airports, ocean surveillance, and research systems, to cite a few. Other types of sensors have recently appeared, which allow [...] Read more.
Radar technology has evolved considerably in the last few decades. There are many areas where radar systems are applied, including air traffic control in airports, ocean surveillance, and research systems, to cite a few. Other types of sensors have recently appeared, which allow tracking sub-millimeter motion with high speed and accuracy rates. These millimeter-wave radars are giving rise to myriad new applications, from the recognition of the material close objects are made, to the recognition of hand gestures. They have also been recently used to identify how a person interacts with digital devices through the physical environment (Tangible User Interfaces, TUIs). In this case, the radar is used to detect the orientation, movement, or distance from the objects to the user’s hands or the digital device. This paper presents a thoughtful comparative analysis of different feature extraction techniques and classification strategies applied on a series of datasets that cover problems such as the identification of materials, element counting, or determining the orientation and distance of objects to the sensor. The results outperform previous works using these datasets, especially when the accuracy was lowest, showing the benefits feature extraction techniques have on classification performance. Full article
(This article belongs to the Special Issue Advances in Applied Signal and Image Processing Technology)
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