Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.5
4.2
Journals
Technologies
Special Issues
Image Analysis and Processing
share announcement

Image Analysis and Processing

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1126

Special Issue Editors

Dr. Xi Li

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
Interests: artificial intelligence and Internet of Things
Dr. Zhongtao Fu

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
Interests: robot theory and algorithms; multimodal perception and learning; Lie groups; Lie algebra
Dr. Yu Shi

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
Interests: computer vision; image analysis and processing; deep learning
Dr. Zhenghua Huang

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
Interests: computer vision; image analysis and processing; deep learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Image analysis and processing is an important branch in the field of computer vision and artificial intelligence, which focuses on how to use computer technology to efficiently process and analyze images in order to extract useful information and meet the needs of specific applications. This field involves image preprocessing, feature extraction, image segmentation, target recognition, image reconstruction, and other aspects. Through the use of mathematics, physics, statistics, and other methods, image analysis and processing technology plays an important role in medical diagnosis, remote sensing monitoring, security monitoring, industrial automation, digital entertainment, and other fields, which brings convenience to human life and, at the same time, promotes the development of related disciplines.

This Special Issue focuses on some of the recent developments in computer vision, artificial intelligence, image preprocessing, feature extraction, image segmentation, target recognition, and image reconstruction.

Potential topics of this Special Issue include but are not limited to the following:

  • Multimodal image denoising and enhancement;
  • Multimodal image fusion;
  • Image classification and semantic segmentation;
  • Object detection and segmentation;
  • Robot dynamics and control;
  • Human–robot interaction;
  • Robot learning;
  • AI for teaching.

Dr. Xi Li
Dr. Zhongtao Fu
Dr. Yu Shi
Dr. Zhenghua Huang
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. Technologies 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 1600 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
  • artificial intelligence
  • image preprocessing
  • feature extraction
  • image segmentation
  • target recognition
  • image reconstruction

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 16547 KiB  
Article
A New Method for Camera Auto White Balance for Portrait
by Sicong Zhou, Kaida Xiao, Changjun Li, Peihua Lai, Hong Luo and Wenjun Sun
Technologies 2025, 13(6), 232; https://doi.org/10.3390/technologies13060232 - 5 Jun 2025
Viewed by 229
Abstract
Accurate skin color reproduction under varying CCT remains a critical challenge in the graphic arts, impacting applications such as face recognition, portrait photography, and human–computer interaction. Traditional AWB methods like gray-world or max-RGB often rely on statistical assumptions, which limit their accuracy under [...] Read more.
Accurate skin color reproduction under varying CCT remains a critical challenge in the graphic arts, impacting applications such as face recognition, portrait photography, and human–computer interaction. Traditional AWB methods like gray-world or max-RGB often rely on statistical assumptions, which limit their accuracy under complex or extreme lighting. We propose SCR-AWB, a novel algorithm that leverages real skin reflectance data to estimate the scene illuminant’s SPD and CCT, enabling accurate skin tone reproduction. The method integrates prior knowledge of human skin reflectance, basis vectors, and camera sensitivity to perform pixel-wise spectral estimation. Experimental results on difficult skin color reproduction task demonstrate that SCR-AWB significantly outperforms traditional AWB algorithms. It achieves lower reproduction angle errors and more accurate CCT predictions, with deviations below 300 K in most cases. These findings validate SCR-AWB as an effective and computationally efficient solution for robust skin color correction. Full article
(This article belongs to the Special Issue Image Analysis and Processing)
►▼ Show Figures

Figure 1

21 pages, 8188 KiB  
Article
New Approach to Dominant and Prominent Color Extraction in Images with a Wide Range of Hues
by Yurii Kynash and Mariia Semeniv
Technologies 2025, 13(6), 230; https://doi.org/10.3390/technologies13060230 - 4 Jun 2025
Viewed by 216
Abstract
Dominant colors significantly influence visual image perception and are widely used in computer vision and design. Traditional extraction methods often neglect visually salient colors that occupy small areas yet possess high aesthetic relevance. This study introduces a method for detecting both dominant and [...] Read more.
Dominant colors significantly influence visual image perception and are widely used in computer vision and design. Traditional extraction methods often neglect visually salient colors that occupy small areas yet possess high aesthetic relevance. This study introduces a method for detecting both dominant and visually prominent colors in a wide range of hues and images. We analyzed the color gamut of images in the CIE L*a*b* color space and concluded that it is difficult to identify the dominant and prominent colors due to high color variability. To address these challenges, the proposed approach transforms images into the orthogonal ICaS color space, integrating the properties of RGB and CMYK models, followed by K-means clustering. A spectral residual saliency map is applied to exclude background regions and emphasize perceptually significant objects. Experimental evaluation on an image database shows that the proposed method yields color palettes with broader gamut coverage, preserved luminance, and visually balanced combinations. A comparative analysis was conducted using the ΔE00 metric, which accounts not only for differences in lightness, chroma, and hue but also for the perceptual interactions between colors, based on their proximity in the color space. The results confirm that the proposed method exhibits greater color stability and aesthetic coherence than existing approaches. These findings highlight the effectiveness of the orthogonal saliency mean method for delivering a more perceptually accurate and visually consistent representation of the dominant colors in an image. This outcome validates the method’s applicability for image analysis and design. Full article
(This article belongs to the Special Issue Image Analysis and Processing)
►▼ Show Figures

Figure 1

23 pages, 5095 KiB  
Article
Human-Machine Interaction: A Vision-Based Approach for Controlling a Robotic Hand Through Human Hand Movements
by Gerardo García-Gil, Gabriela del Carmen López-Armas and José de Jesús Navarro, Jr.
Technologies 2025, 13(5), 169; https://doi.org/10.3390/technologies13050169 - 23 Apr 2025
Viewed by 405
Abstract
An anthropomorphic robot is a mechanical device designed to perform human-like tasks, such as manipulating objects, and has been one of the significant contributions in robotics over the past 60 years. This paper presents an advanced system for controlling a robotic arm using [...] Read more.
An anthropomorphic robot is a mechanical device designed to perform human-like tasks, such as manipulating objects, and has been one of the significant contributions in robotics over the past 60 years. This paper presents an advanced system for controlling a robotic arm using user hand gestures and movements. It eliminates the need for traditional sensors or physical controls by implementing an intuitive approach based on MediaPipe and computer vision. The system recognizes the user’s hand movements. It translates them into commands that are sent to a microcontroller, which operates a robotic hand equipped with six servomotors: five for the fingers and one for the wrist, which stands out for its orthonormal design that avoids occlusion problems in turns of up to 180°, guaranteeing precise wrist control. Unlike conventional systems, this approach uses only a 2D camera to capture movements, simplifying design and reducing costs. The proposed system allows replicating the user’s activity with high precision, expanding the possibilities of human-robot interaction. Notably, the system has been able to replicate the user’s hand gestures with an accuracy of up to 95%. Full article
(This article belongs to the Special Issue Image Analysis and Processing)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop