- 标题
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- 实验方案
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Precision Light Curves from <i>TESS</i> Full-frame Images: A Different Imaging Approach
摘要： The Transiting Exoplanet Survey Satellite (TESS) will observe ～150 million stars brighter than T mag ? , with 16 photometric precision from 60 ppm to 3%, enabling an array of exoplanet and stellar astrophysics investigations. While light curves will be provided for ～400,000 targets observed at 2 minute cadence, observations of most stars will only be provided as full-frame images (FFIs) at 30 minute cadence. The TESS image scale of ～21″/pix is highly susceptible to crowding, blending, and source confusion, and the highly spatially variable point-spread function (PSF) will challenge traditional techniques, such as aperture and Gaussian-kernel PSF photometry. We use official “End-to-End 6” TESS simulated FFIs to demonstrate a difference image analysis pipeline, using a δ-function kernel, that achieves the mission specification noise floor of 60 ppm hr?1/2. We show that the pipeline performance does not depend on position across the field, and only ～2% of stars appear to exhibit residual systematics at the level of ～5 ppt. We also demonstrate recoverability of planet transits, eclipsing binaries, and other variables. We provide the pipeline as an open-source tool at https://github.com/ryanoelkers/DIA in both IDL and PYTHON. We intend to extract light curves for all point sources in the TESS FFIs as soon as they become publicly available, and will provide the light curves through the Filtergraph data visualization service. An example data portal based on the simulated FFIs is available for inspection at https://filtergraph.com/tess_ffi.
关键词： techniques: image processing,catalogs,methods: data analysis
更新于2025-09-23 15:22:29
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Assessment of CT numbers in limited and medium field-of-view scans taken using Accuitomo 170 and Veraviewepocs 3De cone-beam computed tomography scanners
摘要： Purpose: To assess the influence of anatomic location on the relationship between computed tomography (CT) number and X-ray attenuation in limited and medium field-of-view (FOV) scans. Materials and Methods: Tubes containing solutions with different concentrations of K2HPO4 were placed in the tooth sockets of a human head phantom. Cone-beam computed tomography (CBCT) scans were acquired, and CT numbers of the K2HPO4 solutions were measured. The relationship between CT number and K2HPO4 concentration was examined by linear regression analyses. Then, the variation in CT number according to anatomic location was examined. Results: The relationship between K2HPO4 concentration and CT number was strongly linear. The slopes of the linear regressions for the limited FOVs were almost 2-fold lower than those for the medium FOVs. The absolute CT number differed between imaging protocols and anatomic locations. Conclusion: There is a strong linear relationship between X-ray attenuation and CT number. The specific imaging protocol and anatomic location of the object strongly influence this relationship.
关键词： Image Processing, Computer-Assisted,Imaging, Three-Dimensional,Cone-Beam Computed Tomography
更新于2025-09-23 15:22:29
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An intelligent adjustable spanner for automated engagement with multi-diameter bolts/nuts during tightening/loosening process using vision system and fuzzy logic
摘要： The paper presents the development of a novel automated engagement intelligent spanner that is capable of autonomously changing its jaws’ size according to the diameters of the bolt’s/nut’s heads. It is a complete innovative system that involves the utilization of the vision system and fuzzy logic to make decisions about the diameter of head of bolt/nut. Image processing techniques has been implemented to extract the features of the bolts/nut, such as borders, non-borders area, outer diameter, and inner diameter of the head of the bolt/nut. It can be generally divided into three different stages, namely image pre-processing, image processing, and image post-processing. In image pre-processing stage, the image is prepared by applying some operations, such as acquiring streaming video, image cropping, gray-scale transformation, and background separation. Many filters and functions are applied in the image processing stage to efficiently get a clear border for the bolt/nut. In image post-processing, the necessary calculations are applied to get the diameter of the desired bolt, which involves the use of Hough Transformer and fitting circles searching process. The fuzzy logic-based decision-making algorithm is applied to the images resulting from the post-processing stage in order to do a final decision on the diameter of the bolt/nut and approximate it to the nearest standards diameter. Three bolts sizes are used in the experiments, namely M4, M4 with dust; M5; and M6 which are tested with 80 samples (20 for each). The results show the capability of image processing and fuzzy logic algorithms in making the right decisions on the diameter of bolts/nuts with 99% successful rate.
关键词： Vision system,Decision-making,Intelligent spanner,Image processing,Fuzzy logic
更新于2025-09-23 15:22:29
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cuFFS: A GPU-accelerated code for Fast Faraday rotation measure Synthesis
摘要： Rotation measure (RM) synthesis is a widely used polarization processing algorithm for reconstructing polarized structures along the line of sight. Performing RM synthesis on large datasets produced by telescopes like LOFAR can be computationally intensive as the computational cost is proportional to the product of the number of input frequency channels, the number of output Faraday depth values to be evaluated and the number of lines of sight present in the data cube. The required computational cost is likely to get worse due to the planned large area sky surveys with telescopes like the Low Frequency Array (LOFAR), the Murchison Widefield Array (MWA), and eventually the Square Kilometre Array (SKA). The massively parallel General Purpose Graphical Processing Units (GPGPUs) can be used to execute some of the computationally intensive astronomical image processing algorithms including RM synthesis. In this paper, we present a GPU-accelerated code, called cuFFS or CUDA-accelerated Fast Faraday Synthesis, to perform Faraday rotation measure synthesis. Compared to a fast single-threaded and vectorized CPU implementation, depending on the structure and format of the data cubes, our code achieves an increase in speed of up to two orders of magnitude. During testing, we noticed that the disk I/O when using the Flexible Image Transport System (FITS) data format is a major bottleneck and to reduce the time spent on disk I/O, our code supports the faster HDFITS format in addition to the standard FITS format. The code is written in C with GPU-acceleration achieved using Nvidia’s CUDA parallel computing platform. The code is available at https://github.com/sarrvesh/cuFFS.
关键词： Computing methodologies: graphics processors,Techniques: image processing,Techniques: polarimetric,GPGPU,Methods: data analysis
更新于2025-09-23 15:22:29
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Image and data processing algorithms for identifying cell-bound membrane vesicle trajectories and movement information
摘要： This DIB article provides details about the trajectory identification and data processing algorithms used in the article "Dynamic single-vesicle tracking of cell-bound membrane vesicles on resting, activated, and cytoskeleton-disrupted cells" (Zhang et al.) [1]. The algorithm identifies vesicles on cell membranes from series of undyed grayscale images captured by the confocal microscope based on contrast differences and then trajectories of vesicles are obtained by analyzing their positions in consecutive images. Once the trajectories have been obtained, other quantitative movement information, such as moving speed, direction and acceleration, are derived by standard dynamic relations.
关键词： MATLAB algorithms,Vesicle tracking,Trajectory tracing,Confocal microscopy,Image processing
更新于2025-09-23 15:22:29
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Defect detection techniques robust to process variation in semiconductor inspection
摘要： As semiconductor manufacturing process has resulted in downscaling device dimensions, the critical defect size has been becoming smaller and smaller. The highly sensitive optical wafer inspection tool for detecting small defects erroneously detects the process variations as defects and generates a large amount of 'nuisance' information. Thus, the scanning electron microscope (SEM)-based review tool needs to automatically discriminate between defects and nuisance information. To discriminate nuisance information, the absence of defects in the SEM image needs to be accurately detected through an inspection process using the review tool. We propose a defect detection method with (a) an integration of multiple comparison-detection results (IMCD) to suppress the number of defect candidates and (b) a discrimination based on a normal image model (DNPM) to judge whether the candidate is a defect or normal. An evaluation using SEM images of a processed wafer revealed that combining the IMCD and DNPM achieves a nuisance information discrimination rate of 84.4% and a defect detection rate of 93.3%, which are higher than those of the one-class support vector machine (SVM). The proposed methods automatically collect defect images efficiently even when much nuisance information is produced by the optical wafer inspection tool and enable manual visual checks to be reduced.
关键词： image processing,clustering,one-class discrimination,self-organizing map,defect inspection
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA) - Concepcion, Chile (2018.10.17-2018.10.19)] 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA) - Comparison of vegetation indices acquired from RGB and Multispectral sensors placed on UAV
摘要： This manuscript presents a comparison of Normalized Difference Vegetation Index (NDVI) obtained with multispectral cameras versus four indices obtained from RGB sensors for the identification of soil and vegetation in images captured with an unmanned aerial vehicle. This comparison was made using the NDVI as ground truth, obtaining 2 classes of data that would be compared later to the other indexes by counting the pixels corresponding to each class. In the case of the RGB indices, the average was defined as the center of the data and as the cut-off point of both classes. The results of this investigation indicated that it is possible to identify the same spatial patterns using RGB indices, where the TGI index shows the best behavior. However, despite the fact that the pixel count showed similar results, the visual inspection of the results indicated that the RGB indices presented errors when identifying the vegetation, especially in the zone of the row. This indicates that to delimit with precision the areas corresponding to vegetation and soil it is necessary to use more complex clustering techniques.
关键词： Image processing,Agricultural engineering,Unmanned aerial vehicles (UAV)
更新于2025-09-23 15:22:29
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[IEEE 2018 4th International Conference on Computing Sciences (ICCS) - Jalandhar, India (2018.8.30-2018.8.31)] 2018 4th International Conference on Computing Sciences (ICCS) - A Survey on Image Processing Techniques for Seeds Classification
摘要： Agriculture is the department which has shown a rapid growth. Due to this growth today we have a lot of variety of seeds which belongs to the same breed, which may be a result of breed crossover. Now, this has become a challenge to classify the seeds from each other. In another contrast, we have some healthy seeds and some of the seeds becomes defected. One way of separating them from the healthy seeds was, do manually by a team of experts and some manual systems, which is a time consuming and laborious task. So there was need to build a automatic / intelligent system which classify them on the basis of some fixed parameters like shape, length, height, perimeter etc. This paper shows various techniques available for doing the same.
关键词： Fuzzy,Neural Networks,Seed Classification,Computational Intelligence,Feature Extraction,Image Processing
更新于2025-09-23 15:22:29
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[IEEE 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) - Singapore, Singapore (2018.11.18-2018.11.21)] 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) - Camera Based Decision Making at Roundabouts for Autonomous Vehicles
摘要： Being able to join roundabouts correctly is crucial for an autonomous vehicle to maintain not only its own safety but also a normal traffic order for others. In order to know the right time and speed for entering roundabouts, the location, speed and direction of the approaching vehicles need to be taken into consideration. This study investigated the feasibility of leveraging computer vision and machine learning to help autonomous vehicles decide to wait or to enter when reaching roundabouts. A grid-based image processing approach with a single camera at normal roundabouts (GBIPA-SC-NR) is proposed in this paper to characterize traffic situations that can be used for machine learning algorithms to learn the roundabout joining criteria. Video road clips recorded when human drivers reach and then join various roundabouts at different locations were utilised for this learning process, with a selection of four supervised classification algorithms (i.e. the Support Vector Machines, Random Forests, K-Nearest Neighbours, and Decision Tree). The trained classifiers using the proposed approach were evaluated on 507 test videos captured at roundabouts, where the SVM showed the best performance with a 90.28% classification accuracy. This result suggests that the proposed grid-based image processing method can be applied to effectively help autonomous vehicles made the right decision when reaching a roundabout.
关键词： Autonomous Vehicle,Grid-based Image Processing,Machine Learning,Roundabout
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA) - Concepcion, Chile (2018.10.17-2018.10.19)] 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA) - Using clustering algorithms to segment UAV-based RGB images
摘要： This article describes the implementation of two segmentation algorithms in combination with the Triangular Greenness Index (TGI) derived from images obtained from an unmanned aerial vehicle (UAV), with the objective of segmenting shadow, soil and vegetation data obtained from a commercial vineyard cv. Cabernet Sauvignon. The importance of this segmentation lies in the recent development in tools that allow remote monitoring of crops but that nevertheless still have unresolved methodological aspects. The precise differentiation of these classes would allow the development of more complex monitoring techniques based on multispectral and thermal sensors. The results of this investigation showed that both k-means and Clustering Large Applications (CLARA) allowed to differentiate three classes in the images corresponding to soil, shade and vegetation. However, CLARA showed a better performance when differentiating the layer corresponding to vegetation.
关键词： Image processing,Unmanned aerial vehicles,Agricultural engineering,Open source software
更新于2025-09-23 15:22:29