Light Stripe Research Articles

Multi-object distance determination by analysis of CoC variation for dynamic structured light.

A multi-object distance determination method can be achieved by 932 nm structured light with one camera as the data receiver. The structured light generated by a liquid crystal on silicon spatial light modulator (LCoS-SLM) facilitates dynamic image projection on targets. A series of moving light strip images were captured and collected for data analysis. This method lifted the limitation of single-object distance determination and the limitation of the angle requirement between the camera and the light source in the triangulation method. The average error of this method was approximately 3% in the range of 700 mm to 1900 mm away from LCoS-SLM without further optimization. It provides a potential compact design for indoor multi-object distance determination in the future.

A Study on Refraction Error Compensation Method for Underwater Spinning Laser Scanning Three-Dimensional Imaging.

Laser scanning 3D imaging technology, because it can obtain accurate three-dimensional surface data, has been widely used in the search for wrecks and rescue operations, underwater resource development, and other fields. At present, the conventional underwater spinning laser scanning imaging system maintains a relatively fixed light window. However, in low-light situations underwater, the rotation of the scanning device causes some degree of water fluctuation, which warps the light strip data that the system sensor receives about the object's surface. To solve this problem, this research studies an underwater 3D scanning and imaging system that makes use of a fixed light window and a spinning laser (FWLS). A refraction error compensation algorithm is investigated that is based on the fundamentals of linear laser scanning imaging, and a dynamic refraction mathematical model is established based on the motion of the imaging device. The results of the experiment on error analysis in an optimal underwater environment indicate that the error in reconstructing the radius is decreased by 60% (from 2.5 mm to around 1 mm) when compensating for the measurement data of a standard sphere with a radius of 20 mm. Moreover, the compensated point cloud data exhibit a higher degree of correspondence with the model of the standard spherical point cloud. Furthermore, we examine the impact of physical noise, measurement distance, and partial occlusion of the object on the imaging system inside an authentic underwater setting. This study is a good starting point for looking at the refractive error of an underwater laser scanning imaging system. It also provides to us some ideas for future research on the refractive error of other scanning imaging methods.

Design and performance evaluation of a pendulous piezoelectric rotational energy harvester through magnetic plucking of a fan-shaped hanging composite plate

Over the past decade, there has been significant interest in harvesting energy from rotational motion through piezoelectric transduction, with the aim of providing energy-autonomous structural health monitoring systems for rotating machinery. Unlike most existing separated-type magnetically plucked piezoelectric rotational energy harvesters (PREHs) where a separate stationary support is frequently required to place either exciting or excited magnets, we proposed a pendulous piezoelectric rotational energy harvester (P-PREH) which was characterized by the structural integration and simultaneous motion of the piezoelectric transducer and actuator to harvest energy from rotating machines without stationary support. Structure simulation, fabrication, and experimental testing were performed to verify the structural feasibility and investigate the effect of structure and exciting parameters. The results showed that the P-PREH can generate relatively stable output voltage within a wide range of rotary speeds because of the random swing of exciting disk. Besides, the load resistance-dependent power indicated that P-PREH with swing radius of proof mass of 160 mm and the exciting magnet quantity ratio of 0.82 could yield a maximum output power of 0.65 mW at 20 kΩ and 1120 r/min. Also, 50 blue LEDs, array of different color LEDs and a low-power light strip could be lighted by the P-PREH.

Scan-less microscopy based on acousto-optic encoded illumination.

Several optical microscopy methods are now available for characterizing scientific and industrial processes at sub-micron resolution. However, they are often ill-suited for imaging rapid events. Limited by the trade-off between camera frame-rate and sensitivity, or the need for mechanical scanning, current microscopes are optimized for imaging at hundreds of frames-per-second (fps), well-below what is needed in processes such as neuronal signaling or moving parts in manufacturing lines. Here, we present a scan-less technology that allows sub-micrometric imaging at thousands of fps. It is based on combining a single-pixel camera with parallelized encoded illumination. We use two acousto-optic deflectors (AODs) placed in a Mach-Zehnder interferometer and drive them simultaneously with multiple and unique acoustic frequencies. As a result, orthogonal light stripes are obtained that interfere with the sample plane, forming a two-dimensional array of flickering spots - each with its modulation frequency. The light from the sample is collected with a single photodiode that, after spectrum analysis, allows for image reconstruction at speeds only limited by the AOD's bandwidth and laser power. We describe the working principle of our approach, characterize its imaging performance as a function of the number of pixels - up to 400 × 400 - and characterize dynamic events at 5000 fps.

The Collapsible Light Trap: a portable Pennsylvania Light Trap for collecting aquatic insects.

A Collapsible Light Trap (CLT) for collecting insects, particularly aquatic insects, is described here. CLT is a modified Pennsylvania Light Trap with the advantage of being collapsible and lightweight to be carried in a small backpack and very easy to set up in the field. CLT is equipped with LED light strip wrapped around a PVC tube and can be connected to a regular 12 V / 7 Ah battery, running for more than 48 uninterrupted hours. Complete CLT weighs 0.8-1.0 kg, depending on the metal used, and the battery weighs around 2 kg, being easily transportable to more remote collecting areas. Over the years, CLTs have been used for collecting and describing the diversity of aquatic insects from Brazil, particularly caddisflies. Depending on the locality, only one trap for one night can collect over a thousand insect specimens and more than 200 individuals of caddisflies.

Selective α-oxidation of amides via visible-light-driven iron catalysis.

Hydroxyl radicals (˙OH) as one of the highly reactive species can react unselectively with a wide range of chemicals. The ˙OH radicals are typically generated under harsh conditions. Herein, we report hydroxyl radical-induced selective N-α C(sp3)-H bond oxidation of amides under greener and mild conditions via an Fe(NO3)3·9H2O catalyst inner sphere pathway upon irradiation with a 30 W blue LED light strip (λ = 455 nm) using NaBrO3 as the oxidant. This protocol exhibited high chemoselectivity and excellent functional group tolerance. A preliminary mechanism investigation demonstrated that the iron catalyst afforded hydroxyl radicals via the visible-light-induced homolysis (VLIH) of iron complexes followed by a hydrogen atom transfer (HAT) process to realize this transformation.

Underwater Structured Light Stripe Center Extraction with Normalized Grayscale Gravity Method.

The non-uniform reflectance characteristics of object surfaces and underwater environment disturbances during underwater laser measurements can have a great impact on laser stripe center extraction. Therefore, we propose a normalized grayscale gravity method to address this problem. First, we build an underwater structured light dataset for different illuminations, turbidity levels, and reflective surfaces of the underwater object and compare several state-of-the-art semantic segmentation models, including Deeplabv3, Deeplabv3plus, MobilenetV3, Pspnet, and FCNnet. Based on our comparison, we recommend PSPnet for the specific task of underwater structured light stripe segmentation. Second, in order to accurately extract the centerline of the extracted light stripe, the gray level values are normalized to eliminate the influence of noise and light stripe edge information on the centroids, and the weights of the cross-sectional extremes are increased to increase the function convergence for better robustness. Finally, the subpixel-structured light center points of the image are obtained by bilinear interpolation to improve the image resolution and extraction accuracy. The experimental results show that the proposed method can effectively eliminate noise interference while exhibiting good robustness and self-adaptability.

Weld line structured light stripe center extraction approach based on data dimensionality reduction

In order to improve the accuracy and speed of extracting the center of the line structured light stripe when using the vision measurement technology to get the 3D information of the weld sample, this paper proposes a center extraction approach based on the idea of data dimensionality reduction. First, use the weighted gray centroid approach to get the initial center point of the light stripe. Then, build a 7×7 template centered on the pixel block where the initial point is located and performs singular value decomposition on the 49×3 matrix within the template to get the normal direction of the initial point. Finally, calculate the stripe's exact center points through second-order Taylor expansion and smooth repair by cubic spline interpolation of breakpoints. The comparison experimental results show that this approach can effectively reduce the influence of the noise outside the light stripe on the center extraction, reduce the extraction time while ensuring the measurement accuracy, which can lay a good foundation for the point cloud data processing and surface reconstruction.

Rapid detection of avian influenza virus based on CRISPR-Cas12a

BackgroundAvian influenza (AI) is a disease caused by the avian influenza virus (AIV). These viruses spread naturally among wild aquatic birds worldwide and infect domestic poultry, other birds, and other animal species. Currently, real-time reverse transcription polymerase chain reaction (rRT-PCR) is mainly used to detect the presence of pathogens and has good sensitivity and specificity. However, the diagnosis requires sophisticated instruments under laboratory conditions, which significantly limits point-of-care testing (POCT). Rapid, reliable, non-lab-equipment-reliant, sensitive, and specific diagnostic tests are urgently needed for rapid clinical detection and diagnosis. Our study aimed to develop a reverse transcription recombinase polymerase amplification (RT-RPA)/CRISPR method which improves on these limitations.MethodsThe Cas12a protein was purified by affinity chromatography with Ni-agarose resin and observed using sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE). Specific CRISPR RNA (crRNA) and primers targeting the M and NP genes of the AIV were designed and screened. By combining RT-RPA with the Cas12a/crRNA trans-cleavage system, a detection system that uses fluorescence readouts under blue light or lateral flow strips was established. Sensitivity assays were performed using a tenfold dilution series of plasmids and RNA of the M and NP genes as templates. The specificity of this method was determined using H1–H16 subtype AIVs and other avian pathogens, such as newcastle disease virus (NDV), infectious bursal disease virus (IBDV), and infectious bronchitis virus (IBV).ResultsThe results showed that the method was able to detect AIV and that the detection limit can reach 6.7 copies/μL and 12 copies/μL for the M and NP gene, respectively. In addition, this assay showed no cross-reactivity with other avian-derived RNA viruses such as NDV, IBDV, and IBV. Moreover, the detection system presented 97.5% consistency and agreement with rRT-PCR and virus isolation for detecting samples from poultry. This portable and accurate method has great potential for AIV detection in the field.ConclusionAn RT-RPA/CRISPR method was developed for rapid, sensitive detection of AIV. The new system presents a good potential as an accurate, user-friendly, and inexpensive platform for point-of-care testing applications.

Fusing heterogeneous tri-dimensional information for reconstructing submerged structures in harsh sub-sea environments

Exploiting stronger winds at offshore farms leads to a cyclical need for maintenance due to the harsh maritime conditions. While autonomous vehicles are the prone solution for O&M procedures, sub-sea phenomena induce severe data degradation that hinders the vessel’s 3D perception. This article demonstrates a hybrid underwater imaging system that is capable of retrieving tri-dimensional information: dense and textured Photogrammetric Stereo (PS) point clouds and multiple accurate sets of points through Light Stripe Ranging (LSR), that are combined into a single dense and accurate representation. Two novel fusion algorithms are introduced in this manuscript. A Joint Masked Regression (JMR) methodology propagates sparse LSR information towards the PS point cloud, exploiting homogeneous regions around each beam projection. Regression curves then correlate depth readings from both inputs to correct the stereo-based information. On the other hand, the learning-based solution (RHEA) follows an early-fusion approach where features are conjointly learned from a coupled representation of both 3D inputs. A synthetic-to-real training scheme is employed to bypass domain-adaptation stages, enabling direct deployment in underwater contexts. Evaluation is conducted through extensive trials in simulation, controlled underwater environments, and within a real application at the ATLANTIS Coastal Testbed. Both methods estimate improved output point clouds, with RHEA achieving an average RMSE of 0.0097m - a 52.45% improvement when compared to the PS input. Performance with real underwater information proves that RHEA is robust in dealing with degraded input information; JMR is more affected by missing information, excelling when the LSR data provides a complete representation of the scenario, and struggling otherwise.

A three-dimensional vision measurement method based on double-line combined structured light

In this paper, a structured light vision measurement method using a scanning laser line and a positioning laser line is proposed. The novel method enables the scanning laser plane to slide along a slide rail while maintaining intersection with the positioning laser plane, eliminating the need to determine the scanning direction and moving step. During the measurement process, the laser plane equations need to be recalibrated for each new position, so a real-time calibration method is given. Initially, the geometric barycenter method is employed to detect the subpixel coordinates of the light stripe intersection point. Subsequently, these coordinates are projected into the camera coordinate system using the initial equations of the positioning laser plane. Finally, leveraging the normal information of the initial equation of the scanning laser plane and the three-dimensional coordinates of the light stripe intersection point, the real-time calibration of the scanning laser plane equations can be accomplished. The proposed method enables the three-dimensional reconstruction of objects, and its accuracy is verified through measurements on gauge blocks. Experimental results demonstrate that this method achieves precise and stable three-dimensional reconstruction of object surface shape.

Portable IoT-Based Disinfection Box

The COVID-19 pandemic is an ongoing global health event that began in 2019. It is caused by a novel strain of coronavirus known as SARS-CoV-2. Bacteria and viruses can cause illness in human. Therefore, a Portable IoT-based Disinfection Box is developed in this work to disinfect small electronic devices such as smartphone, smartwatch or even a 13-inch tablet, that may come into contact with bacteria and viruses. There are three special features of this Disinfection Box which are the timer itself, Web Interface Monitoring, portable and spacious with dimensions of 29 × 18 × 14 cm3. The ESP32 Wi-Fi module with NodeMCU-32S Base module as a microcontroller is used in this work and it controls the 2-channel Relay in order to turn ON and OFF the UV-C LED light strip. Besides that, it is also connected to the LCD display with I2C module to display the real-time of disinfection process. The Dashboard of Arduino IoT Cloud allows the user to control and monitor the operation of disinfection process. When a small electronic device is placed inside the Disinfection Box, UV-C LED light strip is turned on to begin the disinfection process. The effectiveness of the UV-C LED light strip is investigated by using the Petri dish with agar. It is shown from the experimental procedures that 10-minute disinfection time provided by the Disinfection Box is sufficient to disinfect small electronic devices such as smartphone and smartwatch. This is based on the great reduction of bacteria colonies on the agar in Petri dish after being kept in a dark place with room temperature for 4 days.

Research on the center extraction algorithm of structured light fringe based on an improved gray gravity center method

Abstract In this study, we proposed a fast line-structured light stripe center extraction algorithm based on an improved barycenter algorithm to address the problem that the conventional strip center extraction algorithm cannot meet the requirements of a structured light 3D measurement system in terms of speed and accuracy. First, the algorithm performs pretreatment of the structured light image and obtains the approximate position of the stripe center through skeleton extraction. Next, the normal direction of each pixel on the skeleton is solved using the gray gradient method. Then, the weighted gray center of the gravity method is used to solve the stripe center coordinates along the normal direction. Finally, a smooth strip centerline is fitted using the least squares method. The experimental results show that the improved algorithm achieved significant improvement in speed, sub-pixel level accuracy, and a good structured light stripe center extraction effect, as well as the repeated measurement accuracy of the improved algorithm is within 0.01 mm, and the algorithm has good repeatability.

Three-dimensional reconstruction of mobile binocular stereo vision based on push-broom line structured light for a workpiece surface

Stereo vision technology based on line structured light can effectively solve the problem of a three-dimensional (3D) reconstruction of a smooth surface. A method for 3D reconstruction of mobile binocular stereo vision based on push-broom line structured light for a workpiece surface is presented in this paper. The subpixel coordinates of the light strip centers of the line structured light are obtained by the Steger algorithm while the binocular module moves along the guide rail, and the polar constraint is used to achieve the matching of the extracted light strip centers. As a result, the 3D coordinates of the light strip centers in each location can be calculated because of the known interior and external parameters of the binocular module. To obtain the 3D point cloud data of the entire surface, a relative pose optimization method with respect to the initial frame is proposed, which accurately estimates the pose of the cameras in each location with respect to that in the initial location and unifies the 3D coordinates of the light strip centers in each location to the datum coordinates. The relative pose optimization method first estimates the rough values by using the direct linear transform method, and then iteratively calculates the refined solutions based on the principle of minimizing the re-projection errors. Simulation data and substantial experimental results validate the effectiveness of our method. Our method is compared to the direct linear transform method and the frame-by-frame transfer method, and the root mean square error (RMSE) of the distance from 3D point cloud to fitted plane is used to evaluate the 3D reconstruction accuracy. The repeatability experiment shows that the RMSE from our method is as low as 0.83 mm.

Green and Low-Cost Alkali-Polyphenol Synergetic Self-Catalysis System Access to Fast Gelation of Self-Healable and Self-Adhesive Conductive Hydrogels for Self-Powered Triboelectric Nanogenerators.

Biomass-based hydrogels have attracted great attention in flexible and sustainable self-powered power sources but struggled to fabricate in a green, high-efficiency, and low-cost manner. Herein, a novel and facile alkali-polyphenol synergetic self-catalysis system is originally employed for the fast gelation of self-healable and self-adhesive lignin-based conductive hydrogels, which can be regarded as hydrogel electrodes of flexible triboelectric nanogenerators (TENGs). This synergy self-catalytic system comprises aqueous alkali and polyphenol-containing lignin, in which alkali-activated ammonium persulfate (APS) significantly accelerates the generation of radicals and initiates the polymerization of monomers, while polyphenol acts as a stabilizer to avoid bursting polymerization from inherent radical scavenging ability. Furthermore, multiple hydrogen bonds between lignin biopolymers and polyacrylamide (PAM) chains impart lignin-based hydrogels with exceptional adhesiveness and self-healing properties. Intriguingly, the alkaline conditions not only contribute to the solubility of lignin but also impart superior ionic conductivity of lignin-based hydrogel that is applicable to flexible TENG in self-powered energy-saving stair light strips, which holds great promise for industrial applications of soft electronics.

Laser stripe center extraction method base on Hessian matrix improved by stripe width precise calculation

The line laser measurement technology based on triangulation is widely used in the field of complex surface topography measurement. The key technology of line laser measurement is laser stripe center extraction. For high reflective surfaces, due to the low surface roughness, some areas of the laser stripe image are overexposed, resulting in uneven stripe width distribution, asymmetric light intensity distribution of the stripe cross section, and difficulty in extracting the center of the stripe. In this paper, Laser stripe center extraction method based on Hessian matrix method improved by stripe width is proposed. Firstly, the laser stripe image is preprocessed, the influence of noise in the image is alleviated by image filtering and adaptive threshold segmentation, and the region of interest of the image is extracted to reduce the amount of subsequent calculation. The laser stripe width is calculated based on BPNN and divided into different width intervals. The Gaussian kernel is calculated according to the light stripe width and the Hessian matrix is constructed. The Hessian matrix method is used to roughly extract the center coordinates of the light stripe. Based on the continuity of the light stripe, the center coordinates of the light stripe are weighted and corrected to realize the smooth optimization of the center coordinates of the light stripe. The experimental results show that the proposed light stripe center extraction method is superior to the traditional method under different surface roughness and exposure time conditions, which can effectively improve the measurement accuracy of the sensor.

What feels light to you? An exploration into supplying simple information through a light bar in a highly automated vehicle

As advanced features integrate into vehicle, drivers may feel apprehensive to use them. Providing users information using human-machine interfaces (HMIs) may ease fears; however, in highly automated vehicles, the optimal method of displaying information is unclear. Our study examined how using a light strip to transmit varying degrees of information (none, redundant, or supplemental) impacted trust and acceptance in participants (N = 36) across two drives using self-report and physiological measures. We also analyzed which measures predicted psychological comfort in an exploratory investigation of the largely undefined concept. The results indicated no significant effects suggesting that transmitting information through a light strip and its presence may not impact users. In a regression, only trust significantly explained variance of psychological comfort. Future research would benefit from examining what factors influence psychological comfort. Given our young participant demographic, it is possible future AI users may remain unaffected by additional non-textual HMI displays.

A Method for Extracting a Laser Center Line Based on an Improved Grayscale Center of Gravity Method: Application on the 3D Reconstruction of Battery Film Defects

Extraction of the laser fringe center line is a key step in the 3D reconstruction of linear structured light, the accuracy of which is directly related to the quality of the 3D model. A laser center line extraction method based on an improved gray center of gravity method is proposed to solve the problem of low extraction accuracy. Firstly, a smoothing method is used to eliminate the flat top of the laser line, and the Gaussian curve is adopted to fit the peak position of the curve. Then, the gray threshold is set to automatically extract the laser linewidth, and based on the window opening, the grayscale center of gravity method is improved to extract the coordinates of the center pixel for the second time. Finally, experiments show that the average absolute error of the improved laser line extraction method is 0.026 pixels, which is 2.3 times lower than the gray center of gravity method, 1.9 times lower than the curve fitting method, and the standard error can reach 0.005 pixels. Compared with the gray center of gravity method and the curve fitting method, the influence of gray value change on the center line extraction is more fully considered, and the center of the light strip can be extracted more accurately, achieving sub-pixel accuracy.

A 3D reconstruction method based on one-dimensional galvanometer laser scanning system

The line-structured light galvanometer scanning system projects the laser light strip onto the object by swinging the mirror to realize the 3D profile measurement of the object. It has the advantages of compact structure, fast measurement speed and strong adaptability to complex environments. In this paper, a three-dimensional scanning system based on a line laser, a one-dimensional galvanometer and an industrial camera is constructed, and a new mathematical model of one-dimensional galvanometer laser scanner is derived. On this basis, a high-precision and simple calibration method of the laser scanning system is proposed. Compared with other methods, this method takes into account the rotation angle error caused by the installation of the galvanometer. The whole calibration process only needs a freely moving chessboard instead of a precision electric stage for operation, which is very easy and convenient for on-site use. The experimental results show that the measurement system calibrated by the proposed method has an average relative deviation of 0.14% for the distance measurement of ceramic balls, and successfully achieved 3D reconstruction of plaster objects with complex surfaces and metal parts with high or low reflectivity.

Segmentation of tooth enamel microstructure images using classical image processing and U-Net approaches

IntroductionTooth enamel is the hardest tissue in human organism, formed by prism layers in regularly alternating directions. These prisms form the Hunter–Schreger Band (HSB) pattern when under side illumination, which is composed of light and dark stripes resembling fingerprints. We have shown in previous works that HSB pattern is highly variable, seems to be unique for each tooth and can be used as a biometric method for human identification. Since this pattern cannot be acquired with sensors, the HSB region in the digital photograph must be identified and correctly segmented from the rest of the tooth and background. Although these areas can be manually removed, this process is not reliable as excluded areas can vary according to the individual‘s subjective impression. Therefore, the aim of this work was to develop an algorithm that automatically selects the region of interest (ROI), thus, making the entire biometric process straightforward.MethodsWe used two different approaches: a classical image processing method which we called anisotropy-based segmentation (ABS) and a machine learning method known as U-Net, a fully convolutional neural network. Both approaches were applied to a set of extracted tooth images.ResultsU-Net with some post processing outperformed ABS in the segmentation task with an Intersection Over Union (IOU) of 0.837 against 0.766.DiscussionEven with a small dataset, U-Net proved to be a potential candidate for fully automated in-mouth application. However, the ABS technique has several parameters which allow a more flexible segmentation with interactive adjustments specific to image properties.