ABSTRACT
We present a calibration plate for the binocular vision system, which is composed of a long-wavelength infrared camera and a visible spectrum camera with different resolutions. The calibration plate mainly consists of a white low-temperature aluminum plate with 7×7 round through-holes, a black high-temperature stainless steel plate, and a heating plate. It can be captured by the long-wavelength infrared camera and visible spectrum camera simultaneously. In order to reduce the influence of thermal crosstalk on the edge and angle sharpness of the thermal image of the chessboard calibration plate, we use the round through-holes to replace the black-white squares in the chessboard calibration plate. Based on the fabricated calibration plate, we also propose a related calibration method. The proposed method can quickly detect the calibration plate by using the YOLO-V4 neural network. The affine transformation is performed to get the front view of the calibration plate, and a novel circular detection strategy based on arc level instead of pixel-level is adopted to detect the edges of the round through-holes in the calibration plate. The centers of round through-holes are detected, and the parameters of the cameras are calculated according to the coordinates of the centers in the image coordinate system. The simulation experiments and error analysis have been done to verify the centers detection method. The simulation results show that the error of center detection is always less than 1.4 (pixel). In order to further verify the performance of the calibration plate and the proposed calibration method, a binocular vision system based on long-wavelength infrared camera and visible spectrum camera is fabricated, and the verification experiments have been done. In experiments, our calibration plate and the proposed method are compared with the famous Zhang's method. The calibration's average overall mean errors of the visible spectrum camera and long-wavelength infrared camera are about 0.0126 (pixel) and 0.0238 (pixel), and they are respectively decreased by 78.13% and 81.93% compared with Zhang's method. The re-projection error of the binocular vision system is about 0.548 (pixel), which is decreased by 24.52% compared with Zhang's method. The average calibration time of the proposed method is about 0.26s.
ABSTRACT
In this paper, we propose a continuous wavelet transform and iterative decrement algorithm to decompose the light detection and ranging (LiDAR) full-waveform echoes into a series of components, each of which can be assumed as Gaussian essentially. We calculate the scale of continuous wavelet transform in real time according to the relationship between the center frequency of the mother wavelet and the approximate frequency of the transmitted laser pulse. The approximated frequency is calculated according to the half-width of the effective part of transmitted laser pulse. The positions of the Gaussian model components in the echoes can be precisely predicted according to the positions of the maxima of the continuous wavelet transform coefficient. And the boundary points which locate at the left and right sides of the position of the detected components can be detected. Then, the effective sections can be clipped according to the positions of the boundary points. In order to detect the hidden components which are obscured by the high responses from their adjacent components and estimate the initial parameters, the iterative decrement algorithm is carried out. The initial parameters are fitted by the Levenberg-Marquardt algorithm. In order to verify the proposed method, the simulations and experiments whose data is recorded by our coding LiDAR have been done. The simulations and experiments results indicate that the proposed method exhibits excellent performances, and it is valid for the complex full-waveform echo, which includes serious overlapping components.
ABSTRACT
The light detection and ranging (LIDAR) full-waveform echo decomposition method based on empirical mode decomposition (EMD) and the local-Levenberg-Marquard (LM) algorithm is proposed in this paper. The proposed method can decompose the full-waveform echo into a series of components, each of which can be assumed as essentially Gaussian. The original full-waveform echo is decomposed into the intrinsic mode functions (IMFs) and a final residual by using the EMD first. Then, the average period (Tm¯) and corresponding energy densities (EDs) of all IMFs are calculated. A suitable IMF is selected based on the relationship between the EDs of IMFs and the white-noise theoretical spread lines of the 99% confidence-limit level. The components in the full-waveform echo can be detected according to the positions of the maxima of the selected IMF. The initial parameters are estimated by using local-LM fitting. The initial parameters are fitted by global-LM fitting. Compared to the traditional (zero-crossing) ZC method, the proposed method has strong anti-noise performance. It can precisely detect the components and estimate the initial parameters of the components. The proposed method is verified by using the synthetic data; coding LIDAR recorded data; and Land, Vegetation, and Ice Sensor data.
ABSTRACT
Objective:To determine the equilibrium solubility and n-octanol/water partition coefficients (Papp)of cinnamon acid and cinnamaldehyde. Methods:The equilibrium solubility of cinnamon acid and cinnamaldehyde in different solutions was determined by HPLC,and their n-octanol/water partition coefficients were determined by a shaking flask method combined with HPLC-DAD. Results:When the pH of solution was 7.8,the equilibrium solubility of cinnamon acid was the largest,while that of cinnamaldehyde was the largest in pH 6.8 solution. The scopes of lgPappof cinnamon acid and cinnamaldehyde in different buffer solutions(pH 1.2-7.8) were -1.04-2.27 and 0.29-1.67, respectively, while those in n-octanol/water solvent were 0.85 and 1.26, respectively. Conclusion:The method is simple,accurate and fast to predicate the absorption of chemical components. In gastrointestinal physiological environment,cinnamaldehyde has good absorption, while cinnamon acid is with poor absorption in stomach and with better absorption in intestinal.
ABSTRACT
Abstract A novel luminol electrochemiluminescence strategy based on titanium dioxide/carbon nanotubes ( TiO2/CNTs) nanocomposites for detection of glucose was developed. First, the TiO2/CNTs nanocomposites were prepared by a sol-gel method and modified on the glassy carbon electrode. The electrochemiluminescence ( ECL) signal could be greatly enhanced when the electrode was established by the nanocomposites, which finally resulted in the increased sensitivity. Glucose oxidase calalyzed the oxidation of glucose to form H2 O2 , and the H2 O2 reacted with luminol to produce the ECL signal. Thus the above system was proved to be efficient for glucose detection. The modified electrode exhibited excellent ECL signals and a good linear range of 1. 0í10-7-5. 0í10-6 mol/L with a detection limit of 5. 2í10-8 mol/L towards glucose detection. This strategy was successfully demonstrated as a sensitive, rapid, simple and cost-effective method to detect glucose. Meanwhile, the TiO2/CNTs nanocomposites offered a novel material for the signal enhancement in electrochemiluminescence sensor.
