提高关联成像重构质量的研究

比较基于压缩感知关联成像(CGI)与伪逆关联成像(PGI)两者之间的成像效果差异,探讨形态学权重自适应对关联成像去除噪声的效果。选择不同的图像,通过MATLAB软件开展仿真实验,对目标图像分别采样64、256、512、1 024、2 048、3 000次,首先通过关联成像、基于压缩感知关联成像与伪逆关联成像三种方法重构图像,再对比压缩感知与伪逆两种方法重构图像的效果,以峰值信噪比(PSNR)、相关系数(CC)为量化指标,将基于压缩感知关联成像与伪逆关联成像在不同采样次数下进行对比分析。同时,通过实验分析形态学权重自适应去除关联成像中噪声的效果。伪逆关联成像在低次数采样的情况下比基于压缩感知关联成像的成像效果更好,在高采样次数下,基于压缩感知关联成像的成像效果更好。在实际重构中压缩感知关联成像重构的图像仍有噪声,形态学权重自适应可以有效去除关联成像实验中产生的噪声。     

Optical in-process height measurement system for process control of laser metal-wire deposition

We propose an in-process height measurement system for a weld bead and feedback control system for wire-feeding speed for high-quality laser deposition. Metal additive manufacturing, especially laser metal-wire deposition, is effective for complex shape fabrication and repair processing. However, we must control the gap between a weld bead and a feed wire in an optimal range for high-quality deposition. Conventionally, the Z-stage pitch for multi-layer deposition must be precisely adjusted by each deposition shape. In this paper, we design an in-process height measurement system that is integrated in a laser processing head, which measures the weld bead height by a line section method. We decreased the influence of the intense thermal radiation generated from a melt pool by inserting the band-pass filter of the line beam's wavelength in the imaging system and optimizing its line laser power. Consequently, our system can measure the weld bead height near the melt pool, which is 4 mm in front of it. Next we show that our proposed system can measure the weld bead height during wire-laser metal deposition with 50-μm accuracy by comparing its value to the true value. Finally, we achieved a cylinder shape deposition of 50-mm height, regardless of the Z-stage pitch and the cylinder diameter of the multi-layer deposition, by controlling the wire-feeding speed based on the measured weld bead height.     

基于深度语义分割的多源遥感图像海面溢油监测

针对遥感图像海面溢油区域通常受到斑噪声以及强度不均等因素的影响,从而导致溢油区域监测效果较差的问题,本文引入了深度语义分割的方法,将深度卷积神经网络与全连接条件随机场相结合,形成端对端连接。以Resnet结构为基础,首先通过深度卷积神经网络对多源遥感图像粗分割并作为输入,然后经过改进的全连接条件随机场,利用高斯成对势和平均场近似定理,建立条件随机场形成递归神经网络作为输出。通过多源遥感图像对海面溢油区域进行监测,并利用可见光图像估计溢油区域面积。实验在所建立的多源遥感图像数据集上与其它先进模型进行对比,结果表明本文方法提高了溢油区域的分割精度以及精细细节程度,平均交并比为82.1%,监测效果具有明显地改善。     

Structural,optical and temperature dependent photoluminescence properties of Cr3+-activated LaGaO3 persistent phosphor for optical thermometry

Cr³⁺ doped LaGaO₃ phosphor was prepared by hydrothermal reaction method with post-annealing treatment. XRD pattern showed the pure orthorhombic phase of LaGaO₃ at an annealing temperature of 1000 °C. TEM image showed the particles in the range 40-120 nm. The bandgap energy and Urbach tail increased in the doped sample as compared to the undoped sample as estimated from UV–visible diffuse reflectance spectra. PL excitation spectra showed peaks in UV, blue and orange regions. The emission spectra showed broadband with peaks in the NIR region due to emission from ⁴T₂ and ²E states. The intermediate strength of the crystal field has been calculated from the estimated spectroscopic parameter. The average lifetime was found to be in the ms range. Afterglow decay was also recorded. From the low-temperature PL, the zero phonon line, stokes shift energy, vibrational energy and Huang-Rhys parameter were calculated. With rising the temperature, PL emission peak intensity and lifetime values decreased and FWHM increased because of increased numbers of electrons in ⁴T₂ state and increasing non-radiative transition. Temperature-dependent peak intensity ratios and lifetime values were utilized for temperature sensing applications in below room temperature and above room temperature. The results indicate the possibility of present phosphor to be used as optical nanothermometer.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

Synchronous fluorescence and multivariate classification analysis as a screening tool for determining Sudan I dye in culinary spices

Spices are a globally traded commodity which has been found to be adulterated with forbidden Sudan dyes. This work proposes a screening method for determining the adulteration of paprika varieties (mild, hot and smoked) with Sudan I dye, based on constant-wavelength synchronous fluorescence spectroscopy with multivariate classification. Different wavelength-intervals (Δλ) were evaluated. Classification models were built with Partial Least Squares-Discriminant Analysis (PLS-DA) at two Sudan I dye concentration levels (1 and 5 mg L⁻¹) and they were tested with samples at a lower level (0.5 mg L⁻¹). Classification results were quite satisfactory when a strategy based on first-derivative spectra was used for improving classification results. Δλ = 60 nm was chosen as the optimum wavelength interval giving a 100% of sensitivity and specificity. These results are promising because the risk of assigning adulterated samples as safe to be consumed is highly minimized. The proposed method is feasible, rapid and simple taking advantage of Sudan I fluorescence phenomena in a direct way.     

CO2 detection with CNx thin films deposited on porous silicon

In recent years, porous silicon (PSi) has attracted a great deal of attention for sensing applications. However, the high reactivity of PSi surfaces causes serious problems of stability. In this work, we developed new thin films that can serve as stabilizer of PSi for CO₂ gas sensors development. PSi surface was coated with carbon nitride (CN_x) film which is one of the most important interfering to stabilize the PSi layer. CN_x film was deposited by pulsed laser ablation. The effect of CO₂ gas on the sensor response was investigated for different polarization voltages. The electrical properties of (Al/CN_x/PSi/Si) structure were modified in the presence of the gas. The device shows a high sensitivity against CO₂ gas. Furthermore, the current variation of the sensor as a function of time has been investigated. The results show that the Al/CN_x/PSi/Si structure becomes stable after the first two weeks.