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

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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 6837

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Special Issue Editors

Dr. Xin Zhu

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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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Advances in Optical Sensing, Instrumentation and Systems in Sensors (25 articles)

Published Papers (9 papers)

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Research

16 pages, 9195 KiB

Open AccessArticle

Simulating and Verifying a 2D/3D Laser Line Sensor Measurement Algorithm on CAD Models and Real Objects

by Rok Belšak, Janez Gotlih and Timi Karner

Sensors 2024, 24(22), 7396; https://doi.org/10.3390/s24227396 - 20 Nov 2024

Viewed by 332

Abstract

The increasing adoption of 2D/3D laser line sensors in industrial and research applications necessitates accurate and efficient simulation tools for tasks such as surface inspection, dimensional verification, and quality control. This paper presents a novel algorithm developed in MATLAB for simulating the measurements of any 2D/3D laser line sensor on STL CAD models. The algorithm uses a modified fast-ray triangular intersection method, addressing challenges such as overlapping triangles in assembly models and incorporating sensor resolution to ensure realistic simulations. Quantitative analysis shows a significant reduction in computation time, enhancing the practical utility of the algorithm. The simulation results exhibit a mean deviation of 0.42 mm when compared to real-world measurements. Notably, the algorithm effectively handles complex geometric features, such as holes and grooves, and offers flexibility in generating point cloud data in both local and global coordinate systems. This work not only reduces the need for physical prototyping, thereby contributing to sustainability, but also supports AI training by generating accurate synthetic data. Future work should aim to further optimize the simulation speed and explore noise modeling to enhance the realism of simulated measurements. Full article

(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)

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20 pages, 7281 KiB

Open AccessArticle

Enhancing Open-Space Gas Detection Limit: A Novel Environmentally Adaptive Infrared Temperature Prediction Method for Uncooled Spectroscopy

by Guoliang Tang, Fang Ding, Dunping Li, Bangjian Zhao, Chunlai Li and Jianyu Wang

Sensors 2024, 24(22), 7173; https://doi.org/10.3390/s24227173 - 8 Nov 2024

Viewed by 542

Abstract

Gas cloud imaging with uncooled infrared spectroscopy is influenced by ambient temperature, complicating the quantitative detection of gas concentrations in open environments. To solve the aforementioned challenges, the paper analyzes the main factors influencing detection errors in uncooled infrared spectroscopy gas cloud imaging and proposes a temperature correction method to address them. Firstly, to mitigate the environmental effects on the radiative temperature output of uncooled infrared detectors, a snapshot-based, multi-band infrared temperature compensation algorithm incorporating environmental awareness was developed. This algorithm enables precise infrared radiation prediction across a wide operating temperature range. Validation tests conducted over the full temperature range of 0 °C to 80 °C demonstrated that the prediction error was maintained within ±0.96 °C. Subsequently, temperature compensation techniques were integrated, resulting in the development of a comprehensive uncooled infrared spectroscopy gas cloud imaging detection method. Ultimately, the detection limits for SF6, ethylene, cyclohexane, and ammonia were enhanced by 50%, 33%, 25%, and 67%, respectively. Full article

(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)

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13 pages, 692 KiB

Open AccessArticle

Auto Aligning, Error-Compensated Broadband Collimated Transmission Spectroscopy

by Karsten Pink, Alwin Kienle and Florian Foschum

Sensors 2024, 24(21), 6993; https://doi.org/10.3390/s24216993 - 30 Oct 2024

Viewed by 369

Abstract

Broadband spectral measurements of the ballistic transmission of scattering samples are challenging. The presented work shows an approach that includes a broadband system and an automated adjustment unit for compensation of angular distortions caused by non-plane-parallel samples. The limits of the system in terms of optimal transmission and detected forward scattering influenced by the scattering phase function are investigated. We built and validated a setup that measures the collimated transmission signal in a spectral range from 300 nm to 2150 nm. The system was validated using polystyrene spheres and Mie calculations. The limits of the system in terms of optimal transmission and detected forward scattering were researched. The optimal working parameters of the system, analyzed by simulations using the Monte Carlo method, show that the transmission should be larger than 10% and less than 90% to allow for a reliable measurement with acceptable errors caused by noise and systematic errors of the system. The optimal transmission range is between 25% and 50%. We show that the phase function is important when considering the accuracy of the measurement. For strongly forward-scattering samples, errors of up to 80% can be observed, even for a very small numerical aperture of

6.6 \cdot 10^{- 4}

, as used in our experimental system. We also show that errors increase with optical thickness as the ballistic transmission decreases and the multiscattered fraction increases. In addition, errors caused by multiple reflections in the sample layer were analyzed and also classified as relevant for classical absorption spectroscopy. Full article

(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)

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18 pages, 11414 KiB

Open AccessArticle

Analysis of Field of View for a Moon-Based Earth Observation Multispectral Camera

by Zhitong Yu, Hanlin Ye, Mengxiong Zhou, Feifei Li, Yin Jin, Chunlai Li, Guang Liu and Huadong Guo

Sensors 2024, 24(21), 6962; https://doi.org/10.3390/s24216962 - 30 Oct 2024

Viewed by 448

Abstract

A Moon-based Earth observation multispectral camera provides a unique perspective for observing large-scale Earth phenomena. This study focuses on the analysis of the field of view (FOV) for such a sensor. Unlike space-borne sensors, the analysis of the FOV for a Moon-based sensor takes into account not only Earth’s maximum apparent diameter as seen from the lunar surface but also the Earth’s and the solar trajectory in the lunar sky, as well as the pointing accuracy and pointing adjustment temporal intervals of the turntable. Three critical issues are analyzed: (1) The relationship between the Earth’s apparent diameter and the Earth’s phase angle is revealed. It is found that the Earth’s maximum apparent diameter encompasses the Earth’s full phase, suggesting the FOV should exceed this maximum. (2) Regardless of the location on the lunar surface, a sensor will suffer from solar intrusion every orbital period. Although the Earth’s trajectory forms an envelope during an 18.6-year cycle, the FOV should not be excessively large. (3) To design a reasonable FOV, it is necessary to consider both the pointing accuracy and pointing adjustment temporal interval comprehensively. All these insights will guide future Moon-based Earth observation multispectral camera design. Full article

(This article belongs to the Special Issue Advances in Optical Sensing, Instrumentation and Systems: 2nd Edition)

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18 pages, 10601 KiB

Open AccessArticle

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 564

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 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

Open AccessArticle

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 895

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 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

Open AccessArticle

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 1025

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 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

Open AccessArticle

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 1189

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 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

Open AccessArticle

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 764

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 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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