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Symmetry
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Symmetry/Asymmetry in Computer Vision and Pattern Recognition for Sensing Smart...
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Symmetry/Asymmetry in Computer Vision and Pattern Recognition for Sensing Smart Cities

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 902

Special Issue Editors

Prof. Dr. Hugo Jiménez Hernández

E-Mail Website
Guest Editor
Informatics Faculty, Autonomous University of Querétaro, Querétaro 76230, Mexico
Interests: artificial perception for automatic scene interpretation; non-Turing computing models; associative computing; machine learning
Prof. Dr. Jorge Domingo Mendiola-Santibáñez

E-Mail Website
Guest Editor
Facultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, Mexico
Interests: mathematical morphology; contrast; magnetic resonance imaging
Prof. Dr. Ana Marcela Herrera-Navarro

E-Mail Website
Guest Editor
Informatics Faculty, Autonomous University of Querétaro, Querétaro 76230, Mexico
Interests: image analysis; mathematical morphology; pattern recognition; neural networks

Special Issue Information

Dear Colleagues,

This Special Issue examines symmetry and asymmetry in intelligent analytics methods for video-understanding applications related to smart cities, focusing on automatic generation and semi-supervised and unsupervised models within the domains of computer vision and pattern recognition.

The complexity of problems involving intelligent technologies that make decisions based on vast amounts of city data presents an ongoing challenge in pattern recognition and related disciplines. These areas entail sensing and instrumentation to understand and extract data structures and insights from multiple photosensors.

The diverse applications and profound effects of this field make it a high-impact scientific domain. Therefore, it is essential to support research that promotes innovative and groundbreaking contributions to the advancement of knowledge and technology.

This Special Issue invites researchers and experts to share their latest advances and applications within this knowledge frontier, encompassing both theoretical and technological contributions. Submissions are not limited by page count; however, they must demonstrate a comprehensive understanding of the topic and contribute meaningfully to this Special Issue.

Prof. Dr. Hugo Jiménez Hernández
Prof. Dr. Jorge Domingo Mendiola-Santibáñez
Prof. Dr. Ana Marcela Herrera-Navarro
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 submissions that pass pre-check are 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. Symmetry is an international peer-reviewed open access monthly 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 2400 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

  • computer vision systems
  • pattern recognition
  • symmetry and asymmetry
  • smart cities
  • video understanding
  • video analytics
  • smart sensing

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Published Papers (1 paper)

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Research

19 pages, 13222 KiB  
Article
Connecting Cities: A Case Study on the Application of Morphological Shortest Paths
by Jorge L. Perez-Ramos, Selene Ramirez-Rosales, Daniel Canton-Enriquez, Luis A. Diaz Jimenez, Herlindo Hernandez-Ramirez, Ana M. Herrera-Navarro and Hugo Jimenez-Hernandez
Symmetry 2025, 17(1), 114; https://doi.org/10.3390/sym17010114 - 13 Jan 2025
Cited by 1 | Viewed by 674
Abstract
Navigatingdensely connected networks can be complex due to the different connection structures present within a network. No explicit algorithms are designed specifically for this navigation, so heuristic approaches and existing network systems are often employed. However, this task can become computationally asymmetrical, as [...] Read more.
Navigatingdensely connected networks can be complex due to the different connection structures present within a network. No explicit algorithms are designed specifically for this navigation, so heuristic approaches and existing network systems are often employed. However, this task can become computationally asymmetrical, as the complexity of creating a representation of the city is lower than the complexity involved in identifying a set of feasible paths in a combinatorial order. This paper extends the applicability of morphological approaches to compute the shortest path in smart cities, driven by the complexity and size of the vital communication infrastructure. As is well known, this communication infrastructure changes dynamically, particularly with the evolving connection paths due to continuous population growth. Consequently, efficient communication trajectories can quickly become obsolete. The challenge of computing the best trajectories to respond more quickly to the growing population comes with high computational complexity. This paper presents an application that uses a discrete algorithm designed to compute the shortest path through a morphological approach. Specifically, it seeks to identify the best trajectory within a densely populated city based on a complex density graph. By incorporating morphological approaches into path-search algorithms, we can define a new family of methods that operate in discrete spaces with a morphological representation, resulting in approaches that have lower computational requirements. Other well-known applications in this context include the delivery of resources, such as managing electrical power consumption or minimizing time delays in resource delivery. This task is essential but classified as an NP problem, making it an appropriate scenario for applying the proposed algorithm to navigate a dense graph. The paper highlights the well-known problem of finding the shortest path as one of the potential applications of the introduced algorithm. The algorithm aims to identify the optimal path trajectory within a graph representing a dense city’s real scenario. This discussion compares and contrasts the proposal with other established approaches, highlighting the advantages and characteristics of the proposed method. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Computer Vision and Pattern Recognition for Sensing Smart Cities)
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