Simple and precise calibration of the line-structured light vision system using a planar target.

When calibrating a line-structured light vision system using a planar target, noise easily affects the solution of the coordinates of light stripe points at the camera coordinate frame. Therefore, the planar target must be placed in the measurement space many times to capture more target images for improving calibration stability and achieving relatively high calibration accuracy. This complicates the calibration process. This paper proposes a calibration method considering the measurement baselines of a planar target. The planar target is placed only two times, and two target images are captured correspondingly. A three-point subset is made up of the two calibration points that form the measurement baseline with the longest 2D projection and any other calibration point. In this way, it is less affected by noise when using the three-point subsets to establish the equations. Then, we use the lengths of the measurement baselines provided by all three-point subsets and their 2D projections to solve the coordinates of light stripe points at the camera coordinate frame more accurately to calibrate the line-structured light vision system. Both the simulation and actual experiment results demonstrate the feasibility of our method. Based on our calibration method, the RMS error is 0.035 mm for length measurement and 0.054 mm for height measurement. Compared with other existing methods, our method needs only two target images. It can also achieve more accurate calibration results than the other methods. In addition, our calibration method increases the applicability of the line-structured light measurement method by reducing the number of target swings.

Calibration method for structure parameters of a binocular stereo vision system equipped with polarizers.

For structure parameter calibration of a binocular stereo vision system equipped with polarizers, the optimal calibration polarization angle needs to be determined. There are no corresponding solutions for the determination of the optimal polarization angle of structure parameter calibration. Furthermore, existing research considers the polarization angle that causes the image to possess the lowest brightness (gray value) as the optimal polarization angle. This reduces image contrast, and eventually the texture information of the image is lost, which also affects the accuracy of feature extraction. In this paper, we propose a new calibration method for the structure parameters of a binocular stereo vision system equipped with polarizers. We calculated the pose of the target relative to each camera for different polarization angles. The sum of the object-space errors corresponding to each polarization angle was considered as the evaluation criterion to determine the optimal calibration polarization angle. The calibration of structure parameters was finished using images captured on the premise of the optimal calibration polarization angle. This angle can also be considered as the reference of the polarization angle for measurement. Experiment results show that using the calibration results of our method, the reconstructed length error of a 275×200mm target was less than ±0.052mm, the reconstructed linear displacement error was less than ±0.048mm for the range of 0-30 mm, and the reconstructed rotary angle error was less than ±0.048∘ for the range of-30∘-30∘.

Corneal stromal dehydration and optimal stromal exposure time during corneal refractive surgery measured using a three-dimensional optical profiler.

PURPOSE: To quantitatively analyze human corneal stromal dehydration and estimate proper corneal stromal exposure time during corneal refractive surgery. METHODS: The central thickness changes over time in 34 pieces of human corneal tissue were measured using a white light interferometer. The corneal stromal tissue was obtained by femtosecond laser small incision lenticule extraction. The thickness-time dehydration fitting curves were drawn, and the determination coefficient R2 was calculated. The differences in the fitting curve equation coefficients were compared between the thin and thick lenticule groups. The optimal stromal exposure time was calculated under various conditions, including different optical zones and allowable refractive errors. RESULTS: A water loss variation model was successfully established. Linear and quadratic fitting curves were drawn, and the determination coefficient R2 values were significantly close to 1. The average values of R2 for quadratic curves and linear phases 1, 2, and 3 were 0.998 ± 0.002, 0.995 ± 0.007, 0.996 ± 0.003, and 0.984 ± 0.035, respectively. The optimal stromal exposure time varied under different optical zones and allowable diopter error conditions. Taking the allowable error of 0.50 D and the optical zone size of 6.5 mm as an example, the optimal time was approximately 24 s. CONCLUSIONS: The dehydration rate of the human corneal stroma is nonlinear, and the quadratic stromal thickness-time dehydration fitting curve is more in line with the actual water loss trend. The length of the stroma exposure time may affect the postoperative refractive accuracy after corneal refractive surgery.

Robust and Accurate Vision-Based Pose Estimation Algorithm Based on Four Coplanar Feature Points.

Vision-based pose estimation is an important application of machine vision. Currently, analytical and iterative methods are used to solve the object pose. The analytical solutions generally take less computation time. However, the analytical solutions are extremely susceptible to noise. The iterative solutions minimize the distance error between feature points based on 2D image pixel coordinates. However, the non-linear optimization needs a good initial estimate of the true solution, otherwise they are more time consuming than analytical solutions. Moreover, the image processing error grows rapidly with measurement range increase. This leads to pose estimation errors. All the reasons mentioned above will cause accuracy to decrease. To solve this problem, a novel pose estimation method based on four coplanar points is proposed. Firstly, the coordinates of feature points are determined according to the linear constraints formed by the four points. The initial coordinates of feature points acquired through the linear method are then optimized through an iterative method. Finally, the coordinate system of object motion is established and a method is introduced to solve the object pose. The growing image processing error causes pose estimation errors the measurement range increases. Through the coordinate system, the pose estimation errors could be decreased. The proposed method is compared with two other existing methods through experiments. Experimental results demonstrate that the proposed method works efficiently and stably.

Research on multi-defects classification detection method for solar cells based on deep learning.

Solar cells are playing a significant role in aerospace equipment. In view of the surface defect characteristics in the manufacturing process of solar cells, the common surface defects are divided into three categories, which include difficult-detecting defects (mismatch), general defects (bubble, glass-crack and cell-crack) and easy-detecting defects (glass-upside-down). Corresponding to different types of defects, the deep learning model with different optimization methods and a classification detection method based on multi-models fusion are proposed in the paper. In the proposed model, in order to solve the mismatch problem between the default anchor boxes size of YOLOv5s model and the extreme scale of the battery mismatch defect label boxes, the K-means algorithm was adopted to re-cluster the dedicated anchor boxes for the mismatch defect label boxes. In order to improve the comprehensive detection accuracy of YOLOv5s model for the general defects, the YOLOv5s model was also improved by the methods of image preprocessing, anchor box improving and detection head replacing. In order to ensure the recognition accuracy and improve the detection speed for easy-detecting defects, the lightweight classification network MobileNetV2 was also used to classify the cells with glass-upside-down defects. The experimental results show that the proposed optimization model and classification detection method can significantly improve the defect detection precision. Respectively, the detection precision for mismatch, bubble, glass-crack and cell-crack defects are up to 95.64%, 91.8%, 93.1% and 98.0%. By using lightweight model to train the glass-upside-down defect dataset, the average classification accuracy reaches 100% and the detection speed reaches 13.29 frames per second. The comparison experiments show that the proposed model has a great improvement in detection accuracy compared with the original model, and the defect detection speed of lightweight classification network is improved more obviously, which confirms the effectiveness of the proposed optimization model and the multi-defect classification detection method for solar cells defect detection.

Coupling of (methane + air)-membrane biofilms and air-membrane biofilms: Treatment of p-nitroaniline wastewater.

Membrane biofilm (MBf) technology is a promising biological water treatment process that combines membrane aeration with biofilms. To expand its application in the treatment of toxic organic wastewater, methane/air gas mixture-MBfs ((CH4 + Air)-MBfs) and air-MBfs were coupled to enhance the treatment of p-nitroaniline (PNA) wastewater. Based on exploration of the membrane permeability of methane and oxygen, a hybrid MBf reactor was constructed, and the degradation characteristics of PNA and the coupling effects of (CH4 + Air)-MBfs and air-MBfs were studied. The permeation flux of methane was found to be 1.114 g/(m2 d) when using a methane/air gas mixture at an aeration pressure of 10 kPa, and this result was better than that when methane was used as the aeration gas alone. Aeration with a methane/air gas mixture provided conditions for realizing aerobic methane oxidation; the aerobic methane oxidation that occurred in the (CH4 + Air)-MBfs promoted the reduction of PNA, and the intermediates of PNA degradation were further degraded by the air-MBfs. At an influent PNA membrane area load of 1.67 g/(m2 d), the PNA removal load reached 187.30 g/(m3 d). The coupling of MBfs took advantage of different matrix-based MBfs and promoted the degradation of PNA by utilizing the synergistic effects of various functional microorganisms.

Quantitative Analysis of Human Corneal Lenticule Surface Microstructure Irregularity with 3D Optical Profiler Using White Light Interferometry.

PURPOSE: To quantitatively evaluate the cutting quality of small incision lenticule extraction (SMILE) by measuring human corneal lenticule surface roughness in different areas with white light interferometer. METHOD: A white light interferometer was used to quantitatively measure the corneal lenticule surface roughness in different areas. Sixty-three myopic patients (102 eyes) who underwent SMILE surgery were recruited. The surface roughness of the central, pericentral, and peripheral parts of the corneal lenticule surface was measured in both the anterior and posterior planes. Differences in corneal lenticule surface roughness were analyzed between different myopic groups. RESULTS: The surface roughness of the anterior plane of the corneal lenticule was lower than the posterior plane in various areas (central, pericentral, and peripheral parts) (P < .01). Surface roughness gradually increased from the center to the periphery, in both the anterior and posterior planes (P < .01). There were no significant differences in the surface roughness of the central part in both the anterior and posterior planes between the low and high myopic groups. The surface roughness of the high myopic group was higher than that of the low myopic group in the peripheral part (P < .01). There were no significant differences among the three cylinder-specific groups. There was no significant correlation between two paired eyes. A positive correlation between posterior central surface roughness and the percentage tissue altered score (PTA) was found (r = 0.248, P = .012). CONCLUSIONS: The cutting surface of the corneal lenticule performed by femtosecond laser was evaluated with a white light interferometer and displayed inhomogeneity. Deeper cutting with higher myopia and some intraoperative complications, such as suction loss, may result in larger irregularities.

A novel membrane-aerated biofilter for the enhanced treatment of nitroaniline wastewater: Nitroaniline biodegradation performance and its influencing factors.

Nitroaniline (NA) wastewater is known to be highly toxic and biodegradation-resistant. Based on the principles of molecular oxygen supply and biofilm formation, a novel membrane-aerated biofilter (MABF) combining membrane aeration with a biofilter was established for the first time to treat NA wastewater containing the same concentrations of p-nitroaniline (PNA) and o-nitroaniline (ONA). The NA wastewater treatment performance of the MABF was investigated, and the NA biodegradation characteristics were evaluated. When the influent NA concentration was 120 mg/L, the PNA and ONA removal rates reached 100% and 86.56%, respectively. The NA removal loading reached 111.62 g/m3·d, and the total nitrogen (TN) removal rate reached 82.97%. The synergistic effects of the diverse microorganisms in the membrane-aerated and nonaerated zones of the MABF enhanced the removal of NA and nitrogen. This MABF is an economically efficient and environmentally friendly technology for treating wastewater containing toxic and hazardous organic compounds.