Electronics

Journal Browser

► Journal Browser

Special Issue Editors

Dr. Vignesh Suresh

E-Mail Website
Guest Editor

Research & Development, Alcon Laboratories LLC, Fort Worth, TX 76134, USA
Interests: computer vision; machine vision; deep learning; optical metrology

Dr. Beiwen Li

E-Mail Website1 Website2
Guest Editor

Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA
Interests: superfast 3D optical sensing; multi-scale 3D optical metrology; machine/computer vision; in-situ manufacturing inspection and quality control
Special Issues, Collections and Topics in MDPI journals

Dr. Yi Zheng

E-Mail Website
Guest Editor

Meta Reality Lab Research, Redmond, WA 98052, USA
Interests: 3D imaging; AR/VR; deep learning; computer graphics

Special Issue Information

Dear Colleagues,

Computer vision is a research topic that is actively studied/explored by researchers from various domains. Advancements in image processing methods have paved the way for novel computer vision algorithms. Advanced computer vision methods have enabled automation in surgical procedures in healthcare, the quality inspection of parts in industries etc. The objective of this Special Issue of Electronics is to represent the state-of-the-art research progress in image processing and computer vision methods and their application in various domains. We invite researchers to contribute their original and unique articles, as well as review articles. Topics include, but are not limited to, the following areas:

Object detection;
Semantic segmentation;
Defect detection;
Digital image enhancement;
Advances in machine vision/computer vision;
3D imaging;
Optical metrology;
Fringe analysis;
Applications of 3D imaging.

Dr. Vignesh Suresh
Dr. Beiwen Li
Dr. Yi Zheng
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. Electronics 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 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

detection
segmentation
counting
3D imaging
optical metrology
image processing
image analysis
digital images
deep learning

Published Papers (2 papers)

Download All Papers

Review

Jump to: Other

30 pages, 8442 KiB

Open AccessReview

Single-Image Super-Resolution Challenges: A Brief Review

by Shutong Ye, Shengyu Zhao, Yaocong Hu and Chao Xie

Electronics 2023, 12(13), 2975; https://doi.org/10.3390/electronics12132975 - 06 Jul 2023

Cited by 4 | Viewed by 2577

Abstract

Single-image super-resolution (SISR) is an important task in image processing, aiming to achieve enhanced image resolution. With the development of deep learning, SISR based on convolutional neural networks has also gained great progress, but as the network deepens and the task of SISR becomes more complex, SISR networks become difficult to train, which hinders SISR from achieving greater success. Therefore, to further promote SISR, many challenges have emerged in recent years. In this review, we briefly review the SISR challenges organized from 2017 to 2022 and focus on the in-depth classification of these challenges, the datasets employed, the evaluation methods used, and the powerful network architectures proposed or accepted by the winners. First, depending on the tasks of the challenges, the SISR challenges can be broadly classified into four categories: classic SISR, efficient SISR, perceptual extreme SISR, and real-world SISR. Second, we introduce the datasets commonly used in the challenges in recent years and describe their characteristics. Third, we present the image evaluation methods commonly used in SISR challenges in recent years. Fourth, we introduce the network architectures used by the winners, mainly to explore in depth where the advantages of their network architectures lie and to compare the results of previous years’ winners. Finally, we summarize the methods that have been widely used in SISR in recent years and suggest several possible promising directions for future SISR. Full article

(This article belongs to the Special Issue Recent Advances in Image Processing and Computer Vision)

► Show Figures

Figure 1

Other

Jump to: Review

21 pages, 4920 KiB

Open AccessTutorial

3D Imaging with Fringe Projection for Food and Agricultural Applications—A Tutorial

by Badrinath Balasubramaniam, Jiaqiong Li, Lingling Liu and Beiwen Li

Electronics 2023, 12(4), 859; https://doi.org/10.3390/electronics12040859 - 08 Feb 2023

Cited by 2 | Viewed by 1941

Abstract

The rising global population, in conjunction with the increasing demand, decreasing labor supply, and increasing costs in the agricultural sector, has induced a need for automation in this industry. Many of these tasks are simplified using depth images and are accomplished using the help of 3D sensing technology such as stereo vision and time of flight methods. While there are various merits to these approaches, there is a need for high-speed, high-accuracy 3D profiling approaches in this rapidly advancing industry. Fringe Projection Profilometry is a variation of structured light technology, which has the advantage of having high speed in the kilohertz range, and sub-millimeter accuracy, which could be extremely beneficial for this sector to adopt. In this article, we seek to provide a tutorial on this technology, explain its various principles along with the basic methodology, and expound on its advantages. We demonstrate some example results using soybean roots and spinach leaves to show its utility, discuss potential reasons as to why this has not yet been widely adopted by this industry, review its potential limitations, and examine possible ways those limitations can be addressed so that they do not present a roadblock in its adoption. Full article

(This article belongs to the Special Issue Recent Advances in Image Processing and Computer Vision)

► Show Figures