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Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition
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Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 3755

Special Issue Editors

Dr. Xin Zhu

E-Mail Website
Guest Editor
Biomedical Information Engineering Lab, The University of Aizu, Aizu-Wakamatsu, Fukushima 965-8580, Japan
Interests: biomedical signal; biomedical image; biomedical information processing and medical instrumentation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zhenhe Ma

E-Mail Website
Guest Editor
School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China
Interests: Optical detection and imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The goal of this Special Issue is to introduce recent advances in optical sensing, instrumentation, and systems. This involves medical imaging, virtual reality, 3D reconstruction, automatic driving devices, optical system optimization, internet of things, security facilities, navigation systems, computer vision devices, optical materials, optical battery, and so on.

In this Special Issue entitled “Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition”, we aim to publish papers with theoretical and practical novelties in optical sensing, instrumentation, and systems involving medical imaging, computer vision, machine learning, nature-inspired optimization, 3D reconstruction, and any other possible applications.

Topics of interest include, but are not limited to, the following:

  • Optical coherence tomography in biometrics and diagnosis;
  • The implementation of deep learning in optical systems;
  • The optimization of optical systems using nature-inspired optimization methods;
  • 3D reconstruction of uncalibrated visual system in arbitrary scene;
  • Image and signal processing in optical sensing, instrumentation, and systems;
  • Advance laser technology;
  • Optical networks;
  • Optical communication;
  • Optical sensors;
  • Optical materials;
  • Optical devices;
  • Photoelectric sensing;
  • Optical navigation;
  • Nano-optics technology;
  • Optical sensing and diagnosis;
  • Endoscopic microscopy;
  • Optical imaging;
  • Visual sensing;
  • Computer vision;
  • Optical measurement;
  • AI applications in optical sensing;
  • Spectrum detection and analysis;
  • Fiber sensors;
  • Surface plasmon resonance technology.

Dr. Xin Zhu
Prof. Dr. Zhenhe Ma
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. Sensors 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 2600 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

  • optical coherence tomography (OCT)
  • image processing
  • deep learning
  • binocular vision
  • 3D reconstruction
  • optimization
  • spectral analysis
  • computer vision
  • stereo vision
  • surface plasmon resonance

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

Related Special Issue

Published Papers (5 papers)

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Research

18 pages, 10601 KiB  
Article
The Zero-Velocity Correction Method for Pipe Jacking Automatic Guidance System Based on Fiber Optic Gyroscope
by Wenbo Zhang, Lu Wang and Yutong Zu
Sensors 2024, 24(18), 5911; https://doi.org/10.3390/s24185911 - 12 Sep 2024
Viewed by 246
Abstract
The pipe jacking guidance system based on a fiber optic gyroscope (FOG) has gained extensive attention due to its high degree of safety and autonomy. However, all inertial guidance systems have accumulative errors over time. The zero-velocity update (ZUPT) algorithm is an effective [...] Read more.
The pipe jacking guidance system based on a fiber optic gyroscope (FOG) has gained extensive attention due to its high degree of safety and autonomy. However, all inertial guidance systems have accumulative errors over time. The zero-velocity update (ZUPT) algorithm is an effective error compensation method, but accurately distinguishing between moving and stationary states in slow pipe jacking operations is a major challenge. To address this challenge, a “MV + ARE + SHOE” three-conditional zero-velocity detection (TCZVD) algorithm for the fiber optic gyroscope inertial navigation system (FOG-INS) is designed. Firstly, a Kalman filter model based on ZUPT is established. Secondly, the TCZVD algorithm, which combines the moving variance of acceleration (MV), angular rate energy (ARE), and stance hypothesis optimal estimation (SHOE), is proposed. Finally, experiments are conducted, and the results indicate that the proposed algorithm achieves a zero-velocity detection accuracy of 99.18% and can reduce positioning error to less than 2% of the total distance. Furthermore, the applicability of the proposed algorithm in the practical working environment is confirmed through on-site experiments. The results demonstrate that this method can effectively suppress the accumulated error of the inertial guidance system and improve the positioning accuracy of pipe jacking. It provides a robust and reliable solution for practical engineering challenges. Therefore, this study will contribute to the development of pipe jacking automatic guidance technology. Full article
(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)
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17 pages, 5234 KiB  
Article
Full-Automatic High-Efficiency Mueller Matrix Microscopy Imaging for Tissue Microarray Inspection
by Hanyue Wei, Yifu Zhou, Feiya Ma, Rui Yang, Jian Liang and Liyong Ren
Sensors 2024, 24(14), 4703; https://doi.org/10.3390/s24144703 - 20 Jul 2024
Viewed by 670
Abstract
This paper proposes a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) system based on the tissue microarray (TMA) for cancer inspection for the first time. By performing a polar decomposition on the sample’s Mueller matrix (MM) obtained by a transmissive MMMI system we [...] Read more.
This paper proposes a full-automatic high-efficiency Mueller matrix microscopic imaging (MMMI) system based on the tissue microarray (TMA) for cancer inspection for the first time. By performing a polar decomposition on the sample’s Mueller matrix (MM) obtained by a transmissive MMMI system we established, the linear phase retardance equivalent waveplate fast-axis azimuth and the linear phase retardance are obtained for distinguishing the cancerous tissues from the normal ones based on the differences in their polarization characteristics, where three analyses methods including statistical analysis, the gray-level co-occurrence matrix analysis (GLCM) and the Tamura image processing method (TIPM) are used. Previous MMMI medical diagnostics typically utilized discrete slices for inspection under a high-magnification objective (20×–50×) with a small field of view, while we use the TMA under a low-magnification objective (5×) with a large field of view. Experimental results indicate that MMMI based on TMA can effectively analyze the pathological variations in biological tissues, inspect cancerous cervical tissues, and thus contribute to the diagnosis of postoperative cancer biopsies. Such an inspection method, using a large number of samples within a TMA, is beneficial for obtaining consistent findings and good reproducibility. Full article
(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)
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20 pages, 36354 KiB  
Article
Optoelectronic Strain-Measurement System Demonstrated on Scaled-Down Flywheels
by Matthias Franz Rath, Christof Birgel, Armin Buchroithner, Bernhard Schweighofer and Hannes Wegleiter
Sensors 2024, 24(13), 4292; https://doi.org/10.3390/s24134292 - 1 Jul 2024
Viewed by 777
Abstract
Monitoring the strain in the rotating flywheel in a kinetic energy storage system is important for safe operation and for the investigation of long-term effects in composite materials like carbon-fiber-reinforced plastics. An optoelectronic strain-measurement system for contactless deformation and position monitoring of a [...] Read more.
Monitoring the strain in the rotating flywheel in a kinetic energy storage system is important for safe operation and for the investigation of long-term effects in composite materials like carbon-fiber-reinforced plastics. An optoelectronic strain-measurement system for contactless deformation and position monitoring of a flywheel was investigated. The system consists of multiple optical sensors measuring the local relative in-plane displacement of the flywheel rotor. A special reflective pattern, which is necessary to interact with the sensors, was applied to the surface of the rotor. Combining the measurements from multiple sensors makes it possible to distinguish between the deformation and in-plane displacement of the flywheel. The sensor system was evaluated using a low-speed steel rotor for single-sensor performance investigation as well as a scaled-down high-speed rotor made from PVC plastic. The PVC rotor exhibits more deformation due to centrifugal stresses than a steel or aluminum rotor of the same dimensions, which allows experimental measurements at a smaller flywheel scale as well as a lower rotation speed. Deformation measurements were compared to expected deformation from calculations. The influence of sensor distance was investigated. Deformation and position measurements as well as derived imbalance measurements were demonstrated. Full article
(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)
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16 pages, 4031 KiB  
Article
Self-Calibration for Star Sensors
by Jingneng Fu, Ling Lin and Qiang Li
Sensors 2024, 24(11), 3698; https://doi.org/10.3390/s24113698 - 6 Jun 2024
Viewed by 949
Abstract
Aiming to address the chicken-and-egg problem in star identification and the intrinsic parameter determination processes of on-orbit star sensors, this study proposes an on-orbit self-calibration method for star sensors that does not depend on star identification. First, the self-calibration equations of a star [...] Read more.
Aiming to address the chicken-and-egg problem in star identification and the intrinsic parameter determination processes of on-orbit star sensors, this study proposes an on-orbit self-calibration method for star sensors that does not depend on star identification. First, the self-calibration equations of a star sensor are derived based on the invariance of the interstar angle of a star pair between image frames, without any requirements for the true value of the interstar angle of the star pair. Then, a constant constraint of the optical path from the star spot to the center of the star sensor optical system is defined to reduce the biased estimation in self-calibration. Finally, a scaled nonlinear least square method is developed to solve the self-calibration equations, thus accelerating iteration convergence. Our simulation and analysis results show that the bias of the focal length estimation in on-orbit self-calibration with a constraint is two orders of magnitude smaller than that in on-orbit self-calibration without a constraint. In addition, it is shown that convergence can be achieved in 10 iterations when the scaled nonlinear least square method is used to solve the self-calibration equations. The calibrated intrinsic parameters obtained by the proposed method can be directly used in traditional star map identification methods. Full article
(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)
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14 pages, 4294 KiB  
Article
Pointing Error Correction for Vehicle-Mounted Single-Photon Ranging Theodolite Using a Piecewise Linear Regression Model
by Qingjia Gao, Chong Wang, Xiaoming Wang, Zhenyu Liu, Yanjun Liu, Qianglong Wang and Wenda Niu
Sensors 2024, 24(10), 3192; https://doi.org/10.3390/s24103192 - 17 May 2024
Cited by 1 | Viewed by 578
Abstract
Pointing error is a critical performance metric for vehicle-mounted single-photon ranging theodolites (VSRTs). Achieving high-precision pointing through processing and adjustment can incur significant costs. In this study, we propose a cost-effective digital correction method based on a piecewise linear regression model to mitigate [...] Read more.
Pointing error is a critical performance metric for vehicle-mounted single-photon ranging theodolites (VSRTs). Achieving high-precision pointing through processing and adjustment can incur significant costs. In this study, we propose a cost-effective digital correction method based on a piecewise linear regression model to mitigate this issue. Firstly, we introduce the structure of a VSRT and conduct a comprehensive analysis of the factors influencing its pointing error. Subsequently, we develop a physically meaningful piecewise linear regression model that is both physically meaningful and capable of accurately estimating the pointing error. We then calculate and evaluate the regression equation to ensure its effectiveness. Finally, we successfully apply the proposed method to correct the pointing error. The efficacy of our approach has been substantiated through dynamic accuracy testing of a 450 mm optical aperture VSRT. The findings illustrate that our regression model diminishes the root mean square (RMS) value of VSRT’s pointing error from 17″ to below 5″. Following correction utilizing this regression model, the pointing error of VSRT can be notably enhanced to the arc-second precision level. Full article
(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)
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