Importing Diffusion and Re-Designed Backward Process for Image De-Raining.

In recent years, with the increasing demand for high-quality images in various fields, more and more attention has been focused on noise removal techniques for image processing. The effective elimination of unwanted noise plays a crucial role in improving image quality. To meet this challenge, many noise removal methods have been proposed, among which the diffusion model has become one of the focuses of many researchers. In order to make the restored image closer to the real image and retain more features of the image, this paper proposes a DIR-SDE method with reference to the diffusion models of IR-SDE and IDM, which improve the feature retention of the image in the de-raining process, and then improve the realism of the image for the image de-raining task. In this study, IR-SDE was used as the base structure of the diffusion model, IR-SDE was improved, and DINO-ViT was combined to enhance the image features. During the diffusion process, the image features were extracted using DINO-ViT, and these features were fused with the original images to enhance the learning effect of the model. The model was also trained and validated with the Rain100H dataset. Compared with the IR-SDE method, it improved 0.003 in the SSIM, 0.003 in the LPIPS, and 1.23 in the FID. The experimental results show that the diffusion model proposed in this study can effectively improve the image restoration performance.

Assessing Vehicle Wandering Effects on the Accuracy of Weigh-in-Motion Measurement Based on In-Pavement Fiber Bragg Sensors through a Hybrid Sensor-Camera System.

Weigh-in-motion (WIM) systems are essential for efficient transportation and monitoring parameters such as vehicle number, speed, and weight to ensure regulatory compliance and enhance road safety. Recently, WIM measurements using the Glass Fiber Reinforced Polymer Fiber Bragg Grating (GFRP-FBG) sensors have shown robustness and effectiveness. However, the accuracy of weight evaluation using the WIM systems based on GFRP-FBG sensors can be significantly influenced by the vehicle-wandering effect, which introduces uncertainties in wheel position determination and weight calculations. This paper assessed the impact of vehicle wandering on the accuracy of a WIM measurement system based on GFRP-FBG sensors by utilizing a new hybrid sensor-camera system that integrates roadside cameras and in-pavement GFRP-FBG sensors. The detailed methodology and framework of the developed hybrid system are introduced, followed by field testing on Highway I-94 in the United States. The field testing results indicate that by using the hybrid system, the wheel load detection accuracy of the WIM system based on GFRP-FBG sensors can be controlled to be a Type I or Type III WIM according to the ASTM 1318E-09 standard, with an average accuracy ranging from 87.83% to 94.65%. At the same time, when the wander distance is less than or equal to 9 cm, the developed WIM system proves to be very cost-effective as it only comprises two GFRP-FBG sensors, one temperature FBG sensor, and one camera. These findings indicate the practical potential to enhance the accuracy of WIM systems based on GFRP-FBG sensors designed for highways for low-coast, reliable, and accurate measurements by addressing vehicle wandering effects.

Refractive Index Measurement of Glass with Arbitrary Shape Based on Brewster's Law and a Focusing Probe Beam.

The refractive index is one of the most important parameters of optical glasses and has a significant effect on optical properties. The measurement of optical glasses, especially for optical elements such as lenses, is urgently needed. However, several presented methods require the immersion of the sample in liquid and provide indirect measurements, while others require structural parameters as priori knowledge, which is complex and time-consuming. In this study, a Brewster-Law-based direct and simple measurement method for the refractive index of glasses with arbitrary shapes is proposed, and a laser beam is focused on the surface of the sample as a probe. The incident angle of the chief ray is close to the Brewster angle. The reflected light is collected by an array detector. The refractive index is calculated from the minimum intensity position obtained with image processing. Additionally, a symmetric measurement scheme is proposed to improve the accuracy. Using these methods, a prism and four spherical lens samples with different refractive indices or radii of curvature are tested and error analyses are carried out. Results indicate that the accuracy can reach 10-4.

Exploring Fast Fingerprint Construction Algorithm for Unmodulated Visible Light Indoor Localization.

The study of visible light indoor position has received considerable attention. The visible light indoor position has problems such as deployment difficulty and high cost. In our system, we propose a new fingerprint construction algorithm to simplify visible light indoor position. This method can realize the rapid construction of a visible fingerprint database and prove that the fingerprint database can be used repeatedly in different environments. We proved the theoretical feasibility of this method through theoretical derivation. We carried out extensive experiments in two classic real indoor environments. Experimental results show that reverse fingerprinting can be achieved. In 95% of cases, the positioning accuracy can be guaranteed to be less than 10 cm.

An investigation on the relationship among marbling features, physiological age and Warner-Bratzler Shear force of steer longissimus dorsi muscle.

Researchers nowadays have paid much attention to the relationships between tenderness and marbling, or physiological age. While the marbling was mainly evaluated qualitatively with scores or grades, and rarely related with physiological age. Present study was carried out to analyze the marbling features of longissimus dorsi muscle between the 12th and 13th ribs from 18, 36, 54 and 72 months old Simmental steers were quantitatively described with area and perimeter using computer vision technique. Relationship between Warner-Bratzler Shear force (WBSF), physiological age and the marbling features were examined performing regression analysis. The results revealed that WBSF positively correlated with physiological age, but negatively with marbling area and perimeter. Regression analysis showed that the relationship between the shear force and the steers' age was more close to the quadratic curve (R2 = 0.996) and exponential curve (R2 = 0.957). It was observed during study that marbling grew with steers age. Marbling features were in linear correlation with the steers' age, with R2 = 0.927 for marbling area and R2 = 0.935 for marbling perimeter. The industries in future may speculate beef tenderness and physiological age based on the marbling features (area and perimeter), which can be determined through the online image acquisition system and image processing.

Study on the Extraction of CT Images with Non-Uniform Illumination for the Microstructure of Asphalt Mixture.

An adaptive image-processing method for CT images of asphalt mixture is proposed in this paper. Different methods are compared according to the error analysis calculated between the real gradation and 3D reconstruction gradation. As revealed by the test results, the adaptive image-processing method was effective in carrying out different brightness homogenization processes for each image. The Wiener filter with 7 × 7 size filter was able to produce a better noise reduction effect without compromising image sharpness. Among the three methods, the adaptive image-processing method performed best in the accuracy of coarse aggregate recognition, followed by the ring division method and the global threshold segmentation method. The error of the gradation extracted by the adaptive image-processing method was found to be lowest compared with the real gradation. For a variety of engineering applications, the developed method helps to improve the analysis of CT images of asphalt mixtures.

A simple segmentation and quantification method for numerical quantitative analysis of cells and tissues.

BACKGROUND: Microscopic image analysis based on image processing is required for quantitative evaluation of decellularization. Existing methods are not widely used because of expensive commercial software, and machine learning-based techniques lack generality for decellularization because many high-resolution image data has to be processed. OBJECTIVE: In this study, we developed an image processing algorithm for quantitative analysis of tissues and cells in a general microscopic image. METHODS: The proposed method extracts the color images obtained by the microscope into reference images consisting of grayscale, red (R), green (G), and blue (B) information and transforms each into a binary image. The transformed images were extracted by separating the cells and tissues through outlier noise elimination, logical multiplication and labeling. In order to verify the method, decellularization of porcine arotic valve was performed by the electrical method. Slice samples were obtained by time and the proposed method was applied. RESULTS: The experimental results show that the segmentation of cells and tissues, and quantitative analysis of the number of cells and changes in tissue area during the decellularization process was possible. CONCLUSIONS: The proposed method shows that cell and tissue extraction and quantitative numerical analysis were possible in different brightness of microscopic images.

Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon.

Silicon promotes nodule formation in legume roots which is crucial for nitrogen fixation. However, it is very time-consuming and laborious to count the number of nodules and to measure nodule size manually, which led nodule characterization not to be study as much as other agronomical characters. Thus, the current study incorporated various techniques including machine learning to determine the number and size of root nodules and identify various root phenotypes from root images that may be associated with nodule formation with and without silicon treatment. Among those techniques, the machine learning for characterizing nodule is the first attempt, which enabled us to find high correlations among root phenotypes including root length, number of forks, and average link angles, and nodule characters such as number of nodules and nodule size with silicon treatments. The methods here could greatly accelerate further investigation such as delineating the optimal concentration of silicon for nodule formation.

Segmenting retinal vessels with revised top-bottom-hat transformation and flattening of minimum circumscribed ellipse.

Retinal vessel automatic segmentation plays a great important role for analyzing fundus pathologies like diabetes, retinopathy, and hypertension. In this paper, a novel unsupervised method to automatically extract the vessels from fundus images is introduced. The method proposed a new vessel enhancement approach that we called revised top-bottom-hat transformation for removing the bright lesions for further enhancing vessels in a fundus image, and provides a novel feature that we call flattening of minimum circumscribed ellipse for recognizing a vessel. This method was tested on two publicly available databases DRIVE and STARE, and achieved an average accuracy of 0.9446 and 0.9503, respectively. For pathological cases, the approach reached an accuracy of 0.9435 and 0.9439, respectively. The time complexity approaches (O(n)), which is significantly lower than the state-of-the-art method. Graphical Abstract (GA)-Overview of the steps of the proposed algorithm Step 1: Input. Input a fundus color image. Step 2: Preprocess. The aim of process is to obtain gray image and to filter noise. Step 3: Enhancement and amendment. For improving the segmentation accuracy, a new enhancement and amendment is applied for enhancing the vessels particularly thin vessels and removing the various disturbances. Step 4: Blood vessel segmentation. Step 4.1: Binarization. To identify the blood vessel, the threshold-based method is applied to gain binary images. Step 4.2: Object decomposition. Before blood vessel recognition, we must decompose the binary image into some independent objects. Step 4.3: Calculate the flattening. Calculate the flattening of each of objects. Step 4.4: Blood vessel recognition. Blood vessels are identified by its flattening. Step 5: Output. Output a blood vessel image Graphical Abstract (GA)-Overview of the proposed approach. (a) Input Image. (b) Preprocessing. (c) Top-bottom-hat transformation. (d) Enhancement. (e) Blood vessel segmentation with different thresholds. (f) Blood vessels.

Effect of Freeze-Thaw Cycles on Triaxial Strength Property Damage to Cement Improved Aeolian Sand (CIAS).

Natural aeolian sand has the characteristics of low cohesion and poor water stability. In order to improve its crack resistance properties in the process of freeze-thaw cycles, P.O 42.5 ordinary Portland cement was added to form a mixture called cement improved aeolian sand (CIAS). SEM was used to analyze the microscopic micro-structure of CIAS at different times (7 days and 28 days). The mechanical properties of CIAS samples affected by freeze-thaw cycles were tested in a triaxial instrument, and gray-scale images of the three-phase distribution in the CIAS after freeze-thaw cycling were obtained by computed tomography (CT) scanning technology. The pore characteristic parameters (pore area, fractal dimension, and crack length) were studied by digital image process technique. Based on classical Griffith fracture theory, the development of the crack length and crack width with increasing freeze-thaw cycles is determined. Assuming that the pore area subordinates to the Weibull distribution, the parameters of the Weibull distribution, the damage evolution defined by the elastic modulus attenuation, and the pore area development of CIAS were determined. Research shows the cohesion decreases and internal friction angle increases with increasing cycle numbers. Three development patterns are observed: crack growth, crack closure, and crack merging, and the three patterns interact during freeze-thaw cycling. Furthermore, the fractal dimension of the pore edge fluctuates with the increasing number of freeze-thaw cycles. This work provides a theoretical basis for the application of aeolian sand and develops a method for disaster prevention in applications of freeze-thaw cycling.

Tubular microscaffolds for studying collective cell migration.

Epithelial cells demonstrate different collective migratory modes when encountering two (2D) and three dimensional (3D) microenvironment. While planar micropatterns and constraint have been shown to strongly impact collective cell migration (CCM), how out-of-plane curvature and 3D confinement will affect epithelial organization and dynamics remains largely unknown. This is likely due to lack of proper 3D microscaffolds for studying CCM. In this chapter, we briefly review the latest achievement in microengineering approaches to control 3D microenvironment of epithelial development. Then, we introduce convenient and simple methods of fabricating elastomeric tubular biocompatible microchannels as 3D cell culture scaffolds. Afterwards, we describe in detail the experimental set-up for observing 3D coordinated cell migration on curved surfaces and under spatial constraint. Finally, we provide an approach to analyze 3D dynamics using available techniques for 2D images.

Characterization of Septin Ultrastructure in Budding Yeast Using Electron Tomography.

Septins are essential for the completion of cytokinesis. In budding yeast, Saccharomyces cerevisiae, septins are located at the bud neck during mitosis and are closely connected to the inner plasma membrane. In vitro, yeast septins have been shown to self-assemble into a variety of filamentous structures, including rods, paired filaments, bundles, and rings (Bertin et al. Proc Natl Acad Sci U S A, 105(24):8274-8279, 2008; Garcia et al. J Cell Biol, 195(6):993-1004, 2011; Bertin et al. J Mol Biol, 404(4):711-731, 2010). Using electron tomography of freeze-substituted sections and cryo-electron tomography of frozen sections, we determined the three-dimensional organization of the septin cytoskeleton in dividing budding yeast with molecular resolution (Bertin et al. Mol Biol Cell, 23(3):423-432, 2012; Bertin and Nogales. Commun Integr Biol 5(5):503-505, 2012). Here, we describe the detailed procedures used for our characterization of the septin cellular ultrastructure.

Quantitative characterization of carbon/carbon composites matrix texture based on image analysis using polarized light microscope.

A quantitative characteristic method was proposed for characterizing the matrix texture of carbon/carbon(C/C) composites, which determined the mechanical and physical properties of C/C composites. Based on the cloud theory that was commonly used for uncertain reasoning and the transformation between quantitative and qualitative characterization, so the relationship between the extinction angle and texture types was built by the cloud models for describing the texture of microstructure, moreover, linguistic controllers were established to analyze the matrix texture in accordance with the features of the polarized light microscope (PLM) image. On this basis, the extinction angle could be calculated from the PLM image of the C/C composites. In contrast to the results of measurement, the errors between calculative values and measured values were maintained 1-2° in basically. Meanwhile, the PLM image of C/C composites was segmented by the component, in particular, the matrix with mixed textures was further segmented by the difference of texture. It means that the quantitative characterization of C/C composites matrix based on single PLM image has been realized.

Positioning Standardized Acupuncture Points on the Whole Body Based on X-Ray Computed Tomography Images.

Objective: The goal of this research was to position all the standardized 361 acupuncture points on the entire human body based on a 3-dimensional (3D) virtual body. Materials and Methods: Digital data from a healthy Korean male with a normal body shape were obtained in the form of cross-sectional images generated by X-ray computed tomography (CT), and the 3D models for the bones and the skin's surface were created through the image-processing steps. Results: The reference points or the landmarks were positioned based on the standard descriptions of the acupoints, and the formulae for the proportionalities between the acupoints and the reference points were presented. About 37% of the 361 standardized acupoints were automatically linked with the reference points, the reference points accounted for 11% of the 361 acupoints, and the remaining acupoints (52%) were positioned point-by-point by using the OpenGL 3D graphics libraries. Based on the projective 2D descriptions of the standard acupuncture points, the volumetric 3D acupoint model was developed; it was extracted from the X-ray CT images. Conclusions: This modality for positioning acupoints may modernize acupuncture research and enable acupuncture treatments to be more personalized.