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distect: automatic sample-position tracking for X-ray experiments using computer vision algorithms

JOURNAL OF SYNCHROTRON RADIATION 2024年第PT 6期31卷 1514-1524页

作者： Berg, Michael Furrer, Dirk Thominet, Vincent Wang, Xiaoqiang Zeugin, Stefan Grabner, Helmut Stockinger, Kurt Piamonteze, Cinthia Zurich Univ Appl Sci Sch Engn Zurich Switzerland Paul Scherrer Inst CH-5232 Villigen Switzerland

Soft X-ray spectroscopy is an important technique for measuring the fundamental properties of materials. However, for measurements of samples in the sub-millimetre range, many experimental setups show limitations. Position drifts on the order of hundreds of micrometres during thermal stabilization of the system can last for hours of expensive beam time. To compensate for drifts, sample tracking and feedback systems must be used. However, in complex sample environments where sample access is very limited, many existing solutions cannot be applied. In this work, we apply a robust computer vision algorithm to automatically track and readjust the sample position in the dozens of micrometres range. Our approach is applied in a complex sample environment, where the sample is in an ultra-high vacuum chamber, surrounded by cooled thermal shields to reach sample temperatures down to 2.5 K and in the center of a superconducting split coil. Our implementation allows sample-position tracking and adjustment in the vertical direction since this is the dimension where drifts occur during sample temperature change in our setup. The approach can be easily extended to 2D. The algorithm enables a factor of ten improvement in the overlap of a series of X-ray absorption spectra in a sample with a vertical size down to 70 mu m. This solution can be used in a variety of experimental stations, where optical access is available and sample access by other means is reduced.

关键词： variable temperature inserts sample-position tracking soft X-ray absorption spectroscopy computer vision algorithms sample-position accuracy

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Tracking all traffic - computer vision algorithms for monitoring vehicles, individuals, and crowds

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IEEE ROBOTICS & AUTOMATION MAGAZINE 2005年第1期12卷 29-36页

作者： Maurin, B Masoud, O Papanikolopoulos, NP Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA LSIIT Strasbourg France

This article presents a vision-based system for monitoring crowded urban scenes. The approach combines an effective detection scheme based on optical flow and background removal that can locate vehicles, individual pedestrians, and crowds. The detection phase is followed by the tracking phase that tracks all the detected entities. Traffic objects are not simply tracked but a wealth of information (position, velocity, acceleration/deceleration, bounding rectangle, and shape features) is gathered about them also. Potential applications of the methods include intersection control, traffic data collection, and even crowd control after athletic events. Extensive experimental results for a variety of weather conditions are presented. Future work would focus on methods to deal with shadows and occlusions.

关键词： monitoring systems computer vision algorithms intersections vision-based system tracking schemes traffic objects crowds

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Quantitative detection and sorting of broken kernels and chalky grains in milled rice using computer vision algorithms

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JOURNAL OF FOOD ENGINEERING 2024年 383卷

作者： Fan, Fanghui Chen, Haoran Gao, Yi Mou, Tian Shenzhen Univ Coll Chem & Environm Engn Dept Food Sci & Engn Shenzhen 518060 Peoples R China Shenzhen Univ Shenzhen Univ Med Sch Sch Biomed Engn Shenzhen 518060 Peoples R China Guangdong Prov Key Lab Math & Neural Dynam Syst Dongguan 523000 Peoples R China Marshall Lab Biomed Engn Shenzhen 518060 Peoples R China

The milled rice industry faces challenges in effectively detecting and sorting broken kernels and chalky grains. This paper presents a computer vision approach to detect and characterize broken kernels and chalky grains in three milled rice varieties (HM105, WYD4, and JH6). Broken kernel sorting was validated against an ISO-derived recognition method, while the identification of chalky grains was validated using a DSC to assess thermal behavior. The logistic regression showed a strong discriminatory ability in identifying broken kernels. Unlike the ISO method, logistic regression achieved high sorting accuracy for HM105, WYD4, and JH6. The iterative threshold segmentation algorithm also accurately segmented chalky regions in milled rice grains. Regression analysis revealed a significant positive correlation (R2 >= 0.94) between the chalky region area and Delta H values. Therefore, this study introduces a robust and rapid methodology for quantitatively detecting milled rice, with the potential for automation and intelligentization in rice-based food processes.

关键词： Milled rice quality computer vision algorithms Broken kernels Chalky grains Logistic regression Iterative threshold segmentation

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Analysis of computer vision algorithms to Determine the Quality of Fermented Cocoa (Theobroma Cacao): Systematic Literature Review 2nd

Analysis of Computer Vision Algorithms to Determine the Qual...

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2nd International Conference on ICTs in Agronomy and Environment (CITAMA)

作者： Mite-Baidal, Karen Solis-Aviles, Evelyn Martinez-Carriel, Tayron Marcillo-Plaza, Augusto Cruz-Ibarra, Elicia Baque-Bustamante, Wilmer Agr Univ Ecuador Comp Sci Dept Fac Agr Sci Av 25 Julio & Pio JaramilloPOB 09-04-100 Guayaquil Ecuador

ISBN: (纸本)9783030107284;9783030107277

computer vision techniques have been used for the automation of processes in the agricultural sector due to the benefits obtained such as effectiveness and quality. A clear example is the analysis of cocoa beans quality. The increasing interest of computer vision in this area calls for a clear, systematic overview. In this sense, we present a systematic literature review (SLR) of computer vision algorithms to determine the quality of fermented cocoa in a six-year period: from 2013-2018. The aim of this review is to identify the techniques or computer vision algorithms used to assess fermentation index of cocoa beans for quality control, as well, the main physical and chemical characteristics of the cocoa beans identified through the computer vision algorithms. The results show that the PLS (Partial Least-Squares) algorithm is the most used for the classification of images in a statistical approach. Also, color is the physical parameter that is commonly identified through artificial vision algorithms. Meanwhile, Fat and pH are the chemical parameters most identified by FT-NIR (Fourier transform near-infrared) technology in conjunction with the chemometric technique.

关键词： computer vision computer vision algorithms Image recognition

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An Analysis of Rigid Image Alignment computer vision algorithms

An Analysis of Rigid Image Alignment Computer Vision Algorit...

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作者： Joshi, Rajeshree R Georgia Southern University

学位级别：master

computer vision is a field of computer science that includes methods for acquiring, processing, and analyzing images. Image registration is one of the methods used in the computer vision field to transform different sets of data into one coordinate system to align images. Registration is important in order to be able to compare or integrate the data obtained from multiple measurements. Rigid image alignment is a type of image registration technique used to align two two-dimensional images into a common coordinate system based on two transformation parameters, translation and rotation. Before any comparative studies can be performed on two images acquired at different times, it is crucial to align the two images for correct processing later on. In our research study, we are analyzing the accuracy of registering images using two rigid image alignment algorithms, namely the Principal Axes algorithm and the Fast Fourier Transform (FFT) based phase correlation algorithm. The software for registering images using these two methods is written in MATLAB R2011a. We also compared our results with alignments achieved for the same images using an existing Statistical Parametric Mapping (SPM8) package for registration. Image registration algorithms have been used in many applications and accordingly, algorithms are adopted to suit a particular application. Images used for registration can be derived from different capturing devices like camera, scanner, satellite sensors, etc. Our registration software is based on work with images acquired from a Magnetic Resonance Imaging (MRI) scanner and especially for images taken of a quality assurance (QA) phantom. A QA phantom is used to test the quality of images acquired by measuring different QA parameters on images acquired over a period of time. Images acquired from the MRI scanner at different times are geometrically transformed by rotation and translation. In practice, the maximum angle by which the phantom will get rotated at diff

关键词： ETD Rigid image alignment computer vision algorithms Image registration Principal axes Fast fourier transform FFT Mean square error MSE computer vision Image processing

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Toward accurate and scalable rainfall estimation using surveillance camera data and a hybrid deep-learning framework

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Environmental Science and Ecotechnology 2025年 25卷 100562页

作者： Manuel, Fiallos-Salguero Khu, Soon-Thiam Guan, Jingyu Wang, Mingna School of Environmental Science & Engineering Tianjin University Tianjin 300350 China School of Civil Engineering Tianjin University Tianjin 300072 China

Rainfall measurement at high quality and spatiotemporal resolution is essential for urban hydrological modeling and effective stormwater management. However, traditional rainfall measurement methods face limitations regarding spatial coverage, temporal resolution, and data accessibility, particularly in urban settings. Here, we show a novel rainfall estimation framework that leverages surveillance cameras to enhance estimation accuracy and spatiotemporal data coverage. Our hybrid approach consists of two complementary modules: the first employs an image-quality signature technique to detect rain streaks from video frames and selects optimal regions of interest (ROIs). The second module integrates depthwise separable convolution (DSC) layers with gated recurrent units (GRU) in a regression model to accurately estimate rainfall intensity using these ROIs. We evaluate the framework using video data from two locations with distinct rainfall patterns and environmental conditions. The DSC–GRU model achieves high predictive performance, with coefficient of determination (R²) values ranging from 0.89 to 0.93 when validated against rain gauge measurements. Remarkably, the model maintains strong performance during daytime and nighttime conditions, outperforming existing video-based rainfall estimation methods and demonstrating robust adaptability across variable environmental scenarios. The model's lightweight architecture facilitates efficient training and deployment, enabling practical real-time urban rainfall monitoring. This work represents a substantial advancement in rainfall estimation technology, significantly reducing estimation errors and expanding measurement coverage, and provides a practical, low-cost solution for urban hydrological monitoring. © 2025

关键词： computer vision algorithms Rainfall estimation Regression Spatial-temporal resolution Surveillance video

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A Novel 6G Scalable Blockchain Clustering-Based computer vision Character Detection for Mobile Images

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computers, Materials & Continua 2024年第3期78卷 3041-3070页

作者： Yuejie Li Shijun Li Department of Mathematics and Computer Engineering Ordos Institute of TechnologyOrdos017000China School of Mathematics and Physics North China Electric Power UniversityBeijing102206China School of Electrical Information Hunan University of EngineeringXiangtan411104China

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous *** tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and *** the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly *** can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare *** can control their visual data and grant or revoke access as *** Chinese characters from images can provide convenience in various aspects of people’s ***,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character *** contrast,computer vision technologies have significantly improved image recognition *** paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G *** proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain *** data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character *** the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G *** proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G *** results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional ***

关键词： 6G technology blockchain end-to-end recognition Chinese characters natural scene computer vision algorithms convolutional neural network

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A Review on computer vision Applied to Mechanical Tests in Search for Better Accuracy 10th

A Review on Computer Vision Applied to Mechanical Tests in S...

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10th International Conference on Advanced Computational Engineering and Experimenting (ACE)

作者： Baldner, Felipe de Oliveira Costa, Pedro Bastos Santos Gomes, Juliana Freitas Leta, Fabiana Rodrigues Catholic Univ Petropolis UCP 124-Ctr Petropolis RJ Brazil Minas Gerais Fed Univ UFMG Av Antonio Carlos 6627 Belo Horizonte MG Brazil Natl Inst Metrol Qual & Technol Inmetro Av Nossa Senhora Gracas 50 Duque De Caxias RJ Brazil Fed Fluminense Univ R Passo Patria 156 Niteroi RJ Brazil

ISBN: (纸本)9789811398063;9789811398056

Mechanical tests are used to determine a material's behaviour under certain conditions of stress. computer vision Systems have been used since the 1980s in mechanical tests, with techniques evolving in order to accommodate modern needs. This paper has the purpose of reviewing research that combines computer vision Systems and Mechanical Tests, analysing the main steps for better results from such application.

关键词： computer vision Mechanical tests Image acquisition Lighting conditions computer vision algorithms

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Gesture Therapy: A vision-Based System for Upper Extremity Stroke Rehabilitation

Gesture Therapy: A Vision-Based System for Upper Extremity S...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Enrique Sucar, L. Luis, Roger Leder, Ron Hernandez, Jorge Sanchez, Israel Inst Nacl Astrofis Opt & Electr Luis Enrique Erro 1 Puebla Mexico Univ Nacl Autonoma Mexico Mexico City DF Mexico Inst Nacl Neurol & Neurocirujia Mexico City DF Mexico

ISBN: (纸本)9781424441242

Stroke is the main cause of motor and cognitive disabilities requiring therapy in the world. Therefor it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. We have developed a low-cost vision-based system that allows stroke survivors to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a virtual environment for facilitating repetitive movement training, with computer vision algorithms that track the hand of a patient, using an inexpensive camera and a personal computer. This system, called Gesture Therapy, includes a gripper with a pressure sensor to include hand and finger rehabilitation;and it tracks the head of the patient to detect and avoid trunk compensation. It has been evaluated in a controlled clinical trial at the National Institute for Neurology and Neurosurgery in Mexico City, comparing it with conventional occupational therapy. In this paper we describe the latest version of the Gesture Therapy System and summarize the results of the clinical trail.

关键词： arm movement biomechanics biomedical optical imaging computer vision computer vision algorithms finger rehabilitation gesture therapy gripper grippers hand rehabilitation inexpensive camera intensive movement training medical computing medical image processing occupational therapy patient rehabilitation personal computer pressure sensor pressure sensors trunk compensation upper extremity stroke rehabilitation virtual environment vision-based system

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Autonomous robot vision software design using Matlab toolboxes

Autonomous robot vision software design using Matlab toolbox...

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Conference on Intelligent Robots and computer vision XXII - algorithms, Techniques and Active vision

作者： Tedder, M Chung, CJ Lawrence Technol Univ Southfield MI 48075 USA

ISBN: (纸本)081945561X

The purpose of this paper is to introduce a cost-effective way to design robot vision and control software using Matlab for an autonomous robot designed to compete in the 2004 Intelligent Ground Vehicle Competition (IGVC). The goal of the autonomous challenge event is for the robot to autonomously navigate an outdoor obstacle course bounded by solid and dashed lines on the ground. Visual input data is provided by a DV camcorder at 160 x 120 pixel resolution. The design of this system involved writing an image-processing algorithm using hue, satuaration, and brightness (HSB) color filtering and Matlab image processing functions to extract the centroid, area, and orientation of the connected regions from the scene. These feature vectors are then mapped to linguistic variables that describe the objects in the world environment model. The linguistic variables act as inputs to a fuzzy logic controller designed using the Matlab fuzzy logic toolbox, which provides the knowledge and intelligence component necessary to achieve the desired goal. Java provides the central interface to the robot motion control and image acquisition components. Field test results indicate that the Matlab based solution allows for rapid software design, development and modification of our robot system.

关键词： computer vision algorithms autonomous mobile robots obstacle avoidance fuzzy logic neural networks

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