Image Acquisition Method Research Articles

Gyral and sulcal connectivity in the human cerebral cortex.

The rapid evolution of image acquisition and data analytic methods has established in vivo whole-brain tractography as a routine technology over the last 20 years. Imaging-based methods provide an additional approach to classic neuroanatomical studies focusing on biomechanical principles of anatomical organization and can in turn overcome the complexity of inter-individual variability associated with histological and tractography studies. In this work we propose a novel, reliable framework for determining brain tracts resolving the anatomical variance of brain regions. We distinguished 4 region types based on anatomical considerations: (i) gyral regions at borders between cortical communities; (ii) gyral regions within communities; (iii) sulcal regions at invariant locations across subjects; and (iv) other sulcal regions. Region types showed strikingly different anatomical and connection properties. Results allowed complementing the current understanding of the brain's communication structure with a model of its anatomical underpinnings.

High-speed image acquisition system and image acquisition method of ferroelectric liquid crystal light valve film

As one of the new high-performance products, the ferroelectric liquid crystal light valve has entered people's daily lives and has been widely used. Because of its excellent characteristics, it is widely used in various aspects such as industry and commerce. This paper adopts an experimental analysis method and data analysis method, and aims to break through the existing image acquisition methods by studying ferroelectric liquid crystal light valve film and high-speed image acquisition system, and develop an image acquisition system with faster speed and high-quality performance. According to the experimental results, the system can meet the functional requirements and technical indicators proposed by the design and can operate safely and stably, achieving the expected effect of the design.

Industry-Fit AI Usage for Crack Detection in Ground Steel

We investigated optimal implementation strategies for industrial inspection systems aiming to detect cracks on ground steel billets’ surfaces by combining state-of-the-art AI-based methods and classical computational imaging techniques. In 2D texture images, the interesting patterns of surface irregularities are often surrounded by visual clutter, which is to be ignored, e.g., grinding patterns. Even neural networks struggle to reliably distinguish between actual surface disruptions and irrelevant background patterns. Consequently, the image acquisition procedure already has to be optimised to the specific application. In our case, we use photometric stereo (PS) imaging to generate 3D surface models of steel billets using multiple illumination units. However, we demonstrate that the neural networks, especially in high-speed scenarios, still suffer from recognition deficiencies when using raw photometric stereo camera data, and are unable to generalise to new billets and image acquisition conditions. Only the additional application of adequate state-of-the-art image processing algorithms guarantees the best results in both aspects. The neural networks benefit when appropriate image acquisition methods together with image processing algorithms emphasise relevant surface structures and reduce overall pattern variation. Our proposed combined strategy shows a 9.25% better detection rate on validation data and is 14.7% better on test data, displaying the best generalisation.

Spiral CT Image Characteristics and Differential Diagnosis Secondary Pulmonary Tuberculosis and Lung Cancer Based on Visual Sensors.

Helical CT plain scan has high spatial and area resolution, which is beneficial to the extraction of CT features of pulmonary nodules, and is of great significance for the diagnosis and differential diagnosis of pulmonary diseases. In order to deeply study the role of visual sensor image algorithm in CT image, this paper adopts clinical simulation method, data fusion method, and image acquisition method to collect images, analyze CT image features, and simplify the algorithm and create a CT model that can better diagnose secondary tuberculosis and lung cancer. We selected 45 patients with lung disease in this group, with an average age of 38 years. At the same time, the consistency analysis results of the diameter and plain CT value data of the five groups of cases measured by two observers are between 0.82 and 0.88, which has a good consistency. We could find that the nodule diameters of the five groups of cases were different (F =16.99, P < 0.01), and the difference was statistically significant (P < 0.06), indicating that our data are not only accurate but also very reliable. ROC was used to analyze the precise value of CT values in the pulmonary tuberculosis group and lung cancer group, intrapulmonary lymph node group, and pulmonary hamartoma group to determine the cutoff value. The results showed that the AUC values of the pulmonary tuberculosis group and the lung cancer group were 0.788, and the middle was the largest, indicating that the values were guaranteed. The basic realization starts with visual sensor technology and designs a clinical model that can more accurately identify CT images and differential diagnosis.

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition.

PurposeMyocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera.MethodsA clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated.ResultsThe MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth.ConclusionThe continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

Artificial intelligence in ophthalmology: an insight into neurodegenerative disease.

The aging world population accounts for the increasing prevalence of neurodegenerative diseases such as Alzheimer's and Parkinson's which carry a significant health and economic burden. There is therefore a need for sensitive and specific noninvasive biomarkers for early diagnosis and monitoring. Advances in retinal and optic nerve multimodal imaging as well as the development of artificial intelligence deep learning systems (AI-DLS) have heralded a number of promising advances of which ophthalmologists are at the forefront. The association among retinal vascular, nerve fiber layer, and macular findings in neurodegenerative disease is well established. In order to optimize the use of these ophthalmic parameters as biomarkers, validated AI-DLS are required to ensure clinical efficacy and reliability. Varied image acquisition methods and protocols as well as variability in neurogenerative disease diagnosis compromise the robustness of ground truths that are paramount to developing high-quality training datasets. In order to produce effective AI-DLS for the diagnosis and monitoring of neurodegenerative disease, multicenter international collaboration is required to prospectively produce large inclusive datasets, acquired through standardized methods and protocols. With a uniform approach, the efficacy of resultant clinical applications will be maximized.

Customized root-analogue dental implants - Procedure and errors associated with image acquisition, treatment, and manufacturing technology in an experimental study on a cadaver dog mandible

The global market for dental implants is constantly evolving. To overcome the limitations of conventional strategies – invasive surgeries and bone loss around the implant-, new approaches, namely the development of CAD/CAM customized implants, are emerging as promising solutions for replacing missing teeth, thus avoiding destruction of bone by drilling it. Despite the efforts that are being carried out, the designing, including image acquisition, and manufacturing efficacy of such rehabilitation therapy is not easily found in the literature. In this sense, this research work aimed to assess the errors associated with the image acquisition, treatment and manufacturing of Customized Root-Analogue Implants (CRAI). The experimental procedure, carried out in a dog cadaveric mandible, encompassed the image acquisition and treatment and the subsequent manufacturing of four different CRAI. Two Image acquisition methods (CBCT and X-ray), and different software for their treatment were used, and the final CRAI were manufactured by Computer Numerical Control. Results revealed the CBCT scan allowed to properly visualize the original teeth contours. However, all the obtained teeth geometries presented smaller surface areas when compared to the original teeth indicating however a systematic predictable error. On the other hand, when comparing the surface area of the digital and the manufactured teeth, very small differences were observed, which indicates that the CNC manufacturing technique is a promising solution for such applications. When placing the produced CRAI in the dog mandible it was possible to observe a lack of congruency between the CRAI and bone, mainly due to image acquisition process errors and the destruction of the periodontal ligament during the soft tissues removal process. Thus, CBCT images seem to be a feasible route to design root-analogue implants, and, if needed, a compensation strategy for the systematic image acquisition error may be implemented.

2D speckle tracking: a diagnostic and prognostic tool of paramount importance.

We aimed to conduct a review of the literature relevant to cardiac imaging techniques and summarize the use of different non-invasive imaging modalities in the assessment of ventricular size, function, and mechanics. The current review emphasizes the benefits of speckle tracking imaging (STI), highlighting its use in demonstrating myocardial strain. This robust technique is a recent addition to the existing imaging techniques that are used to assess the myocardium. In terms of effectively determining the left ventricle ejection fraction, it is a comparable technique to cardiac magnetic resonance. The use of STI method for image acquisition relies on semiautomatic identification of the border and deformation of the region of interest, and is also independent of the angle of insonation, thus it increases the inter-and intra-observer reproducibility in contrast to the conventional tissue doppler imaging. The databases of PubMed, Scopus, and Embase were thoroughly searched for the following keywords: 2- dimensional/ two-dimensional/ 2-D, speckle/strain tracking, systolic dysfunction, and heart failure. The studies selected described image acquisition techniques and the application of this imaging modality in various clinical settings. The selected journal articles were perused to provide the best possible analysis of STI. Our comparative analysis demonstrated that the STI, when compared with the conventional echocardiography, is a more sensitive image acquiring technique for detecting subclinical myocardial dysfunction. Based on the analysis it can be stated that the STI can provide valuable information on both regional and global myocardial function, and it can also quantify cardiac synchronicity and rotation. Additionally, it serves as a better prognostic indicator. The change in longitudinal strain can serve as an early marker of the left ventricular systolic dysfunction, and therefore, monitoring via STI has both diagnostic and prognostic value in heart failure, ischemic heart disease, valvulopathies, chemotherapy-induced cardiotoxicity, and cardiac resynchronization therapy. Despite the lack of standardization, the method is also effective in assessing the right ventricle and left atrial function and arterial rigidity.

MP09-20 PROSTATE BIOPSY TARGETED TO PROSTATE SPECIFIC MEMBRANE ANTIGEN (PSMA) FOCI

You have accessJournal of UrologyCME1 May 2022MP09-20 PROSTATE BIOPSY TARGETED TO PROSTATE SPECIFIC MEMBRANE ANTIGEN (PSMA) FOCI David Kuppermann, Jeremie Calais, Wayne Brisbane, Elizabeth Tran, Lorna Herbert, Matthias Benz, Johannes Czernin, and Leonard Marks David KuppermannDavid Kuppermann More articles by this author , Jeremie CalaisJeremie Calais More articles by this author , Wayne BrisbaneWayne Brisbane More articles by this author , Elizabeth TranElizabeth Tran More articles by this author , Lorna HerbertLorna Herbert More articles by this author , Matthias BenzMatthias Benz More articles by this author , Johannes CzerninJohannes Czernin More articles by this author , and Leonard MarksLeonard Marks More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002531.20AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: PSMA PET imaging is the most accurate imaging method known for detection of metastatic PCa. PSMA PET may also reveal intra-prostatic cancer. 68Ga-PSMA scanning was approved by FDA in December 2020 for pre-op staging of PCa and to detect possible recurrence. MRI-guided biopsy (MRGB) is the preferred method for diagnosis of prostate cancer (PCa), but PCa may be MRI-invisible (≈15-20%). Herein we study intra-prostatic PSMA focal uptake as a target for biopsy detection of PCa using PET/CT-US fusion (PSMA-guided biopsy, PSMA-GB). METHODS: In a prospective trial, 13 men underwent PSMA PET/CT imaging prior to fusion biopsy at UCLA. Subjects are men with negative prior biopsy (10 MRGB), but continued clinical suspicion of PCa and focal uptake of PSMA in the prostate. Method of PSMA-GB is identical to MRGB (PMID 26749141) but employs US fusion with PET/CT instead of MRI, as detailed previously (PMID: 28607878). Method of Ga-PSMA image acquisition via PET/CT scanning has been reported (PMID: 30920593). Contouring of intra-prostatic foci of PSMA positivity was via Profuse software by co-author J.C. Image fusion & trans-rectal targeted biopsy was via Artemis device (LSM). Detection rate of csPCa ( >GG2) by PSMA-GB was primary endpoint. RESULTS: To date, 13 men have completed study. Median age=71 yrs.; prostate volume=27.7 cc (IQR 22.1, 38.3); PSA density=0.25 ng/ml/cc (IQR 0.10, 0.45 PSMA-GB was successfully completed in all 13 with no more difficulty than usual MRI-GB. Overall detection rate was 9/13 (70%): GG2 in 1, GG3 in 6, and GG4 in 2. Max Cancer Core Length was 4 mm median (IQR 3, 9). 4 PSMA foci were anterior; all 4 contained csPCa. Median SUVmax (standardized uptake value) was 6 in PSMA lesions returning <GG1 findings vs 8.2 in men with csPCa. Median PSAD (density) was higher in men with csPCa (0.25) than others (0.20). Of 5 men with prior radiation, 4 had csPCa on PSMA-GB. CONCLUSIONS: Prostate biopsy, which targets PSMA “hot spots” via PET/CT-US fusion, may lead to detection of clinically significant cancers missed by MRI-guided biopsy. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e144 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information David Kuppermann More articles by this author Jeremie Calais More articles by this author Wayne Brisbane More articles by this author Elizabeth Tran More articles by this author Lorna Herbert More articles by this author Matthias Benz More articles by this author Johannes Czernin More articles by this author Leonard Marks More articles by this author Expand All Advertisement PDF DownloadLoading ...

Partition harvesting of a column-comb litchi harvester based on 3D clustering

Accurate recognition of litchi fruits in orchard environments and acquisition of their coordinate position information are key for realizing successful harvesting using litchi harvesters. However, the existing detection methods are often aimed at large and relatively sparse fruits and thus are inappropriate for small and densely distributed litchi fruits. Therefore, at present, litchi fruit are typically manually harvested, resulting in a low harvesting efficiency that cannot meet the needs of growers. To improve the efficiency of litchi harvesting, this study proposes a column-comb litchi harvesting method based on K-means 3D clustering partitioning, which includes four main steps: (1) Litchi image acquisition and labeling methods are developed. (2) An improved version of the present YOLOv3-tiny network model structure is developed named the YOLOv3-tiny-Litchi network model, and the litchi fruit detection results of five kinds of neural networks, namely, YOLOv3-tiny, YOLOv3-tiny-Litchi, YOLOv4, YOLOv5x and Faster R-CNN, are compared. (3) A depth camera is used to obtain the 3D coordinates of litchi fruits, and the K-means clustering algorithm is used to divide the litchi harvesting area to obtain the optimal partitioning results. (4) Field experiments on litchi harvesting are reported. The experimental results show that the improved YOLOv3-tiny-Litchi model can recognize litchi fruits more accurately; the recall rate is 78.99%, the precision rate is 87.43%, and the F1 score is 0.83. The results of 3D clustering partitioning show that when K is equal to 6, the optimal harvesting rate is 90.03%, which satisfies the theoretical requirements of litchi harvesters. The field experiments show that when the theoretical number of partitions is 6, the average harvesting rate of the litchi harvester is 91.15% and the recognition rate is 88.39%, and the harvesting efficiency of mechanical partition harvesting is 1.4 times that of mechanical harvesting without partitioning and 2 times that of manual harvesting, essentially meeting the operating requirements. These research results can serve as a reference for the mechanization of litchi harvesting.

A high-efficiency acquisition method of LED multispectral images using Gray code based square wave frequency division modulation

LED illumination-based multispectral imaging (LEDMSI) is a fast, convenient, and effective multispectral image acquisition technique. The square wave frequency division modulation (SFDM) and the integral sampling of the camera can build an efficient match pattern. With regards to image quality decline problems due to the ringing effect caused by the drive module while square wave high-low level conversion in the SFDM-LEDMS system. This paper proposes a multispectral image acquisition method combining Gray code and square wave frequency modulation. The micro control unit was used to generate a series of frequency division square waves in Gray code mode followed by LEDs of different wavelengths modulated by SFDM-square waves as a light source. Subsequently, the camera was used to simultaneously collect a sequence of multi-spectral images followed by single-wavelength images using differential accumulation demodulation. Finally, the no-reference image quality assessment (NR-IQA) was used to evaluate the quality of each single-wavelength image obtained by Binary code and Gray code. We deployed five wavelengths as examples to verify the effectiveness of the proposed method. The accumulated results indicated an improvement of the image quality in terms of information and gradient using Gray code. In conclusion, the present study can provide an effective image acquisition alternative for household medical equipment.

Post-processing calcium subtraction method to minimize stenosis-overestimation by blooming artifact.

BACKGROUND: CT images are often affected by blooming artifacts during the diagnosis that facilitate an overestimation of the expression of calcification stenosis, thereby impeding the accurate diagnosis of this condition.OBJECTIVE: Arterial calcification can act as a blooming artifact in computed tomography (CT) images, leading to overestimations of the blood vessel and the size of calcified plaque. This study proposes an improved CT post-processing method that accurately measures calcium and lumen size in blood vessels.METHODS: Six hundred and thirty calcium datasets were obtained from 63 patients diagnosed with a vascular disease. Patients were grouped into three sets corresponding to each image acquisition method used: G1, for the invasive coronary angiography (ICA); G2, for multiplanar reconstruction (MPR) imaging and post-processing; and G3, for the novel method of mixed Gaussian filter and K-mean clustering (GK). Results of GK were generated by adding Gaussian and k-mean clustering algorithms to the MPR post-processing procedure. The analysis of variance (ANOVA), linear regression, and intraclass correlation coefficient (ICC) were used to compare the accuracy and sensitivity of the different methods. All measurements were performed multiple times to mitigate human error.RESULTS: The ANOVA test revealed no significant differences between the G1 and G3 groups. Hence, linear regression was used to analyze the correlation between the G1 and G3 groups ( 0.05, R2 0.885), and a higher correlation than G1 and G2 was reported ( 0.05, R2 0.432). ICC was performed for reproducibility, wherein high correlation was identified among all groups.CONCLUSIONS: Results of the study indicate that the GK method yields images that are very similar to ICA image measurements. This suggests that the GK can be used as a more effective post-processing method over the inaccurate MPR while remaining non-intrusive when determining the arterial stenosis degree, unlike the ICA.

Design of a deep learning visual system for the thickness measurement of each coating layer of TRISO-coated fuel particles

In the new generation of nuclear energy system, the thickness of the coating layer of tristructural isotropic (TRISO)-coated fuel particles is one of the most important parameters. Recently, some visual-based methods have been developed for the thickness measurement of each coating layer, but the existing method still lacks of practicality. In this study, an advanced visual system combined with the ceramographic section method and deep learning algorithms is designed to automatically measure the thickness values of each coating layer. In the designed visual system, an automatic image acquisition method is first achieved. After that, an accurate thickness measurement method is proposed based on the designed image segmentation model. Finally, to enhance the reliability and consistency of the measurement results, a tracing method is developed for the designed measurement system. The experimental results demonstrate that the designed system can accurately automatically measure the thickness values of each coating layer.

Multi-angle excited MOI and image processing strategies specified for detection of orthogonal weld defects.

This paper develops an integrative scheme combining new image acquisition, filtering and enhancement methods specified for orthogonal weld defect detection based on magneto-optical imaging (MOI) technique. For image acquisition, a controllable magnetic system enabling rotation of magnetic angles is invented to accurately collect MO images. Multiple images are acquired, yet few are utilized for further processing in the conventional method based on human subjective preferences, bearing chances that images containing defects are discarded. Therefore, we turn to an automated-filtering system to scrutinize MO images and filter effective images through Bhattacharyya coefficient screening method. This not only elevates efficiency and objectivity but also eliminates missed inspection. For image enhancement, normalization method is used to balance the image intensity, followed by image fusion and edge extraction by a two-dimensional gradient method. Our pre- and post-processing approaches significantly improve accuracy in defect recognition and precision in MO images.

MRI Distortion Correction and Robot-to-MRI Scanner Registration for an MRI-Guided Robotic System.

Magnetic resonance imaging (MRI) guided robotic procedures require safe robotic instrument navigation and precise target localization. This depends on reliable tracking of the instrument from MR images, which requires accurate registration of the robot to the scanner. A novel differential image based robot-to-MRI scanner registration approach is proposed that utilizes a set of active fiducial coils, where background subtraction method is employed for coil detection. In order to use the presented preoperative registration approach jointly with the real-time high speed MRI image acquisition and reconstruction methods in real-time interventional procedures, the effects of the geometric MRI distortion in robot to scanner registration is analyzed using a custom distortion mapping algorithm. The proposed approach is validated by a set of target coils placed within the workspace, employing multi-planar capabilities of the scanner. Registration and validation errors are respectively 2.05 mm and 2.63 mm after the distortion correction showing an improvement of respectively 1.08 mm and 0.14 mm compared to the results without distortion correction.

High-Spatial-Resolution Nighttime Light Dataset Acquisition Based on Volunteered Passenger Aircraft Remote Sensing

Remotely sensed nighttime light (NTL) data provides an opportunity to observe human economic activities at night. However, existing NTL remote sensing data does not sufficiently reflect human activities at a fine resolution. In this study, we obtain a set of NTL data comprising volunteered passenger aircraft nighttime remote sensing (VPAN-RS) imagery by adopting a passenger plane as the remote sensing platform and using low-cost portable photography equipment as sensors. This method demonstrates the advantages of VPAN-RS data in high spatial resolution, frequent revisits, and low cost, which can supplement existing NTL data. The dataset acquired in this study covers 16 cities in China and one city in Japan, with a spatial resolution up to meter level. The data acquisition method and processing workflow are introduced in this article. Quality assessment shows that the reprojection error of the dataset falls within the range from 5–10 pixels, and the geometric error can be within 15 m. Via a comparison to reference data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor of the Suomi-National Polar-Orbiting Partnership (NPP) polar-orbiting satellite, we found that the VPAN-RS data provides more details of city lighting. Additionally, the radiance of the VPAN-RS data suitably fits that of monthly composite NPP/VIIRS data. We further outline an application example of VPAN-RS nighttime imagery, examine the unique challenges associated with VPAN-RS data with a focus on the influence of the image acquisition method on the data quality, and provide an outlook for the future of VPAN-RS data. We conclude that VPAN-RS NTL images are an effective data source for nighttime earth observations and have the potential for various applications.

Filtering and Enhancement Method of Ancient Architectural Decoration Image based on Neural Network

Due to poor ambient light or uneven lighting, the old decoration image acquisition methods are easy to cause the image blur. To solve this problem, this paper proposes a neural network-based filtering enhancement method for ancient architectural decoration images, which preserves image details by enhancing contrast, smoothing noise reduction and edge sharpening. Based on the convolutional neural network which is composed of encoder, decoder and layer hop connection, the residual network and hole convolution are introduced, and the hole U-Net neural network is constructed to fuse the pixel feature blocks of different levels. This method enhanced the image contrast according to the gray level and frequency histogram, and aiming at the gray value of the pixel to be processed in the image. And the middle value of the gray value of the neighborhood pixel is used to filter the noise of the ancient building decoration image. The paper also analyzes the joint strength of beams and columns in ancient buildings, and calculates the elastic constants of beams and columns and the stress at the joint of them, considering the image texture characteristics of the wood in ancient buildings with the mortise and tenon connection of beams and columns. Experimental results show that the proposed method has good noise suppression performance, can effectively obtain image detail features, and significantly improve the subjective visual effect of ancient architectural decoration images.

Random Speckle Projection Image Acquisition Method for Coarse-grained Reflective Surface

Random Speckle Projection Image Acquisition Method for Coarse-grained Reflective Surface

Application of ImageJ Software in the assessment of flowering Intensity and growth Vigor of Pear Trees

Abstract The study evaluated the possibility of using the image acquisition and processing method with ImageJ software for estimating growth vigor and flowering intensity of ‘Conference’ pear trees. For assessing flowering intensity, manual counting of flower clusters and taking of photographs of the trees were conducted at full bloom. Tree vigor was estimated by manually measuring the total length of the central leader and shoots of individual trees. The trees were photographed from the same distance using a hand-held camera. The calibration model for assessing the vigor or flowering of trees by image analysis was based on measurements and photographs taken for nine selected trees differing in the total length of shoots or in the number of flower clusters. Then, a quality assessment of the model was carried out on 26 nonselected trees. Image processing was performed using ImageJ software. High regression coefficients were obtained between the surface area of petals measured on the photographs and the number of inflorescences counted (r2 = 0.98); however, observations carried out in the following year indicate the need for individual calibration of estimation models in each evaluation season. Subsequently, the quality of estimating the flowering intensity of pear trees was assessed using a previously determined calibration model. Mean absolute percentage error (MAPE) values ranged from 14.0% to 21.8%, depending on the measurement time. In the assessment of tree growth vigor, a high correlation (r2 = 0.98) was also obtained between the actual length of shoots measured individually for each tree and the values obtained by analyzing the photographic image, where the MAPE error was 12.9%.

ОЦЕНКА ДЕФЕКТОВ ПОВЕРХНОСТИ ИЗДЕЛИЙ С ПОМОЩЬЮ ЦИФРОВЫХ ТЕХНОЛОГИЙ

The suggested approach provides an opportunity under the conditions of enterprises to give a comprehensive view of products defects and functional coatings imperfections. The application of the computer program developed in the Microsoft Visual Studio environment, which allows digital image processing of the studied surfaces to estimate the area of external defects of materials, regardless of the nature of the origin of defects and the method of image acquisition, is proved.&#x0D; Research methods. Digital images of metal surfaces and coatings obtained by energy dispersive microanalysis, electron and optical microscopy have been tested.&#x0D; Research results and novelty. The possibility of using the program for evaluation of surface bands with local chemical and morphological inhomogeneities, determination of the porosity of materials is shown. The possibility of express evaluation of digital images of objects at macro-, meso- and microstructural levels for automated diagnostic control of surface defects within 1-2 seconds is implemented. Disaggregation of brightness, texture and color components of the image significantly increases the speed and efficiency of image processing structures.&#x0D; Conclusions: The proposed program is versatile, does not require special user skills and serves as a convenient tool for analyzing and controlling the quality of objects of various physico-chemical nature. The results of the study indicate that the application of the developed computer program makes effective quantitative calculation of the area of local defects, areas of distribution of chemical elements, various inclusions, surface porosity of products and coatings possible.