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A pre-processing technique to decrease inspection time in glass tube production lines

IET IMAGE PROCESSING 2021年第10期15卷 2179-2191页

作者： De Vitis, Gabriele Antonio Foglia, Pierfrancesco Prete, Cosimo Antonio Univ Pisa Dipartimento Ingn Informaz Via Diotisalvi 2 I-56100 Pisa Italy

In case of glass tube for pharmaceutical applications, high-quality defect detection is made via inspection systems based on computer vision. The processing must guarantee real-time inspection and meet increasing rate and quality requirements. Defect detection in glass tubes is complicated by aspects that hamper the efficiency of state-of-the-art techniques. This paper presents a pre-processing algorithm which excludes portions of the image where defects are surely absent. The approach decreases the time for defect detection and classification phases (any detection algorithm can be applied), as they are applied only in high-probability candidate sub-image. We derive a methodology to get robust values of algorithm's parameters during production. The algorithm relies on detrended standard deviation and double threshold hysteresis, which solve issues related to the misalignment between illuminator and acquisition camera, and enable a robust detection despite rotation, vibration, and irregularities of tubes. We consider Canny, MAGDDA, and Niblack algorithms. The solution keeps the detection quality of such algorithms and reaches a 4.69x throughput gain. It represents a methodology to obtain defect detection in time-constrained environments through a software-only approach, and can be exploited in parallel/accelerated solutions and in contexts where a linear camera is utilized on both flat and uneven surfaces.

关键词： robust detection detection algorithm time constrained environments probability quality requirements high probability candidate subimage automatic optical inspection preprocessing technique image sensors Niblack algorithms glass products inspection systems production engineering computing high quality defect detection preprocessing algorithm computer vision inspection time glass tube production lines image coding detection quality quality control real-time inspection

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A Maximum Likelihood Perspective of Spatial Filter Design in SSVEP-Based BCIs

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2021年第9期68卷 2706-2717页

作者： Wang, Zhenyu Zhao, Xi Zhang, Min Hu, Honglin Chinese Acad Sci Shanghai Adv Res Inst Shanghai 201210 Peoples R China Univ Chinese Acad Sci Beijing Peoples R China ShanghaiTech Univ Sch Informat Sci & Technol Shanghai Peoples R China

In steady-state visual-evoked potential (SSVEP) based brain-computer interfaces (BCIs), existing detection algorithms utilizing spatial filters like task-related component analysis (TRCA) derive the spatial filters mainly through maximizing the inter-trial similarity between the combined signals over the training set. Although they achieve by far the best classification performance in SSVEP-based BCIs, some important problems are still unresolved. Especially, the mechanism of how spatial filters cancel the background noise in brain signals and optimize the signal-to-noise ratio (SNR) of SSVEPs is still not figured out. Therefore, to solve these problems, in this paper a new perspective of spatial filter design is proposed. Specifically, a linear generative signal model of SSVEP is adopted and the spatial filters are obtained automatically through maximum likelihood estimation of source signals and channel vectors. In the same time, the relation between maximum likelihood estimation and signal-to-noise ratio (SNR) maximization is discussed. Through a step-by-step formulation, this paper provides a theoretical justification for those conventional algorithms utilizing spatial filters. As for the classification performance, the proposed scheme is tested on a benchmark dataset of 35 subjects. Experiment results show that the classification performance of the proposed scheme is competitive against three benchmark algorithms, which include TRCA. Especially, the proposed scheme achieves a fair performance improvement over the benchmark methods in the cases where a shorter time window, or a larger number of electrodes, or a smaller number of training blocks are adopted.

关键词： Correlation Training detection algorithms Signal to noise ratio Maximum likelihood estimation Task analysis Maximum likelihood detection BCI detection algorithm maximum likelihood estimation SNR maximization SSVEP spatial filter

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Enhanced statistical detection of random telegraph noise in frequency and time domain

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SOLID-STATE ELECTRONICS 2022年 194卷

作者： Gauthier, Owen Haendler, Sebastien Scheer, Patrick Vernhet, Alexandre Rafhay, Quentin Theodorou, Christoforos STMicroelectronics 850 Rue Jean Monnet F-38920 Crolles France Univ Savoie Mt Blanc Univ Grenoble Alpes CNRS Grenoble INPIMEP LAHC F-38000 Grenoble France

In this work, a new statistical detection method of Random Telegraph Noise (RTN) in the frequency domain is presented. An algorithm for the automated detection of Lorentzian spectra in the noise power spectral density (PSD) of a device is proposed, which enables the processing of a large amount of experimental data. Using 40 nm Bulk CMOS technology as a test vehicle, we demonstrate that the detection of Lorentzian spectra in the noise PSD allows an easier, faster, and often more precise detection of RTN presence compared to the time domain detection.

关键词： Random telegraph noise Lorentzian noise detection algorithm Statistical analysis CMOS transistor

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Automated detection and Characterization of ESD-Induced Soft Failures Using Image- and Audio-Based Methods

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IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY 2020年第4期62卷 1546-1554页

作者： Izadi, Omid Hoseini Meiguni, Javad Araki, Kenji Shumiya, Hideki Pommerenke, David J. Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA Sony Global Mfg & Operat Corp Tokyo 1080075 Japan Graz Univ Technol Inst Elect A-8010 Graz Austria

Audio- and image-based soft failure detection methods are developed, which can detect both severe failures (such as system hang) and subtle ones (such as glitch or a momentary disturbance on display). Incorporating the developed detection methods with a robotic ESD (electrostatic discharge) tester, we developed a fully automated soft failure investigation tool. Using this fully automated tool, we obtained failure-specific susceptibility maps for a camera (our target device). These susceptibility maps not only illustrated the sensitive locations of the device, they also showed what type of soft failure is correlated with which locations.

关键词： Electrostatic discharges Image edge detection Probes Webcams Strips Robots Automatization detection algorithm electrostatic discharge (ESD) immunity test signal processing soft failure susceptibility map

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Apoptosis detection via automated algorithms to analyze biomarker translocation in reporter cells

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BIOTECHNOLOGY AND BIOENGINEERING 2020年第5期117卷 1470-1482页

作者： Ahmed, A. H. Rezwanuddin Dereli-Korkut, Zeynep Lee, Joanne Haeun Piracha, Sidra Gilchrist, M. Lane Jiang, Xuejun Wang, Sihong CUNY City Coll Dept Biomed Engn New York NY 10031 USA CUNY City Coll Dept Chem Engn New York NY 10031 USA Mem Sloan Kettering Canc Ctr Cell Biol Program 1275 York Ave New York NY 10021 USA

Rapid, efficient, and robust quantitative analyses of dynamic apoptotic events are essential in a high-throughput screening workflow. Currently used methods have several bottlenecks, specifically, limitations in available fluorophores for downstream assays and misinterpretation of statistical image data analysis. In this study, we developed cytochrome-C (Cyt-C) and caspase-3/-8 reporter cell lines using lung (PC9) and breast (T47D) cancer cells, and characterized them from the response to apoptotic stimuli. In these two reporter cell lines, the spatial fluorescent signal translocation patterns served as reporters of activations of apoptotic events, such as Cyt-C release and caspase-3/-8 activation. We also developed a vision-based, tunable, automated algorithm in MATLAB to implement the robust and accurate analysis of signal translocation in single or multiple cells. Construction of the reporter cell lines allows live monitoring of apoptotic events without the need for any other dyes or fixatives. Our algorithmic implementation forgoes the use of simple image statistics for more robust analytics. Our optimized algorithm can achieve a precision greater than 90% and a sensitivity higher than 85%. Combining our automated algorithm with reporter cells bearing a single-color dye/fluorophore, we expect our approach to become an integral component in the high-throughput drug screening workflow.

关键词： biomarker translocation caspase-3 caspase-8 cytochrome-C detection algorithm reporter cells

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Accurate Fiducial Point detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation

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IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2020年 8卷 1900711页

作者： Singla, Muskan Azeemuddin, Syed Sistla, Prasad Int Inst Informat Technol Ctr VLSI & Embedded Syst Technol Hyderabad 500032 India Care Hosp Care Fdn Hyderabad 500034 India

Pulse Arrival Time (PAT) derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) for cuff-less Blood Pressure (BP) measurement has been a contemporary and widely accepted technique. However, the features extracted for it are conventionally from an isolated pulse of ECG and PPG signals. As a result, the estimated BP is intermittent. Objective: This paper presents feature extraction from each beat of ECG and PPG signals to make BP measurements uninterrupted. These features are extracted by employing Haar transformation to adaptively attenuate measurement noise and improve the fiducial point detection precision. Method: the use of only PAT feature as an independent variable leads to an inaccurate estimation of either Systolic Blood Pressure (SBP) or Diastolic Blood Pressure (DBP) or both. We propose the extraction of supplementary features that are highly correlated to physiological parameters. Concurrent data was collected as per the Association for the Advancement of Medical Instrumentation (AAMI) guidelines from 171 human subjects belonging to diverse age groups. An Adaptive Window Wavelet Transformation (AWWT) technique based on Haar wavelet transformation has been introduced to segregate pulses. Further, an algorithm based on log-linear regression analysis is developed to process extracted features from each beat to calculate BP. Results: The mean error of 0.43 and 0.20 mmHg, mean absolute error of 4.6 and 2.3 mmHg, and Standard deviation of 6.13 and 3.06 mmHg is achieved for SBP and DBP respectively. Conclusions: The features extracted are highly precise and evaluated BP values are as per the AAMI standards. Clinical Impact: This continuous real-time BP monitoring technique can be useful in the treatment of hypertensive and potential-hypertensive subjects.

关键词： Adaptive algorithm blood pressure detection algorithm electrocardiography feature extraction photoplethysmography regression analysis signal processing wavelet transforms

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Modeling of Wood Macrostructure in the Technology of Its Cutting 7th

Modeling of Wood Macrostructure in the Technology of Its Cut...

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7th International Conference on Industrial Engineering, ICIE 2021

作者： Isaev, S. Erenkov, O. Pacific National University 136 Tikhookeanskaya Street Khabarovsk680035 Russia

ISBN: (纸本)9783030852290

The work presents general approaches to the construction of the software and hardware stable complex. The complex is capable to detect textural annual rings of round timber with subsequent the object internal macrostructure reconstruction based on the data obtained. The complex constructions are based on algorithms for processing binary and grayscale images using algorithms for identifying informative features and applying the Hough transform. The complex using is aimed to provide tools for simplifying the round timber cutting process and visualizing of its cutting results in the required form. The work reflects the results of creating the round timber macrostructure reconstruction and visualization model with the functions variety for changing the shape and size of the object. The possibility of constructing sections both in 2D and in 3D is achieved also it is possible to obtain the surfaces projections in the plane of sections. Such results allow visually evaluate the round timber texture pattern in a specific coordinate plane in the of round timber volume. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cutting Technology detection algorithm Imitation Macrostructure Modeling Software Module Wood

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Improved detection of faint streaks based on a streak-like spatial filter

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ADVANCES IN SPACE RESEARCH 2020年第1期65卷 364-378页

作者： Vananti, A. Schild, K. Schildknecht, T. Univ Bern Astron Inst Sidlerstr 5 CH-3012 Bern Switzerland

This paper presents an algorithm to detect very faint object streaks on CCD images acquired with an optical system. The proposed detection method uses image filters simulating the geometrical form and orientation of possible streaks on the CCD image. The method searches for a matching between streak and filter evaluating the convolutions of the image with all possible filters. Based on the statistics of the image background a threshold is applied in order to accept, respectively reject, the possible streak candidates. The detection probabilities and the effect of different parameter settings are estimated with tests on simulated images, while subframes of real images are used to evaluate the applicability of the algorithm to real cases. The detection probability of this method depends on the length and on the signal-to-noise ratio of the streak. For long streaks, a detection for signal-to-noise values around 0.5 is achieved. The further characterization of the detected streak (e.g. centroid and length), which is not performed in the current algorithm, and the reduction of the computation time, which is relatively high for full acquired frames, as well as possible improvements are briefly addressed. (C) 2019 COSPAR. Published by Elsevier Ltd. All rights reserved.

关键词： Streak detection detection algorithm Image processing Space debris

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An Improved New YOLOv7 algorithm for Detecting Building Air Conditioner External Units from Street View Images

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SENSORS 2023年第22期23卷 9118页

作者： Tian, Zhongmin Yang, Fei Qin, Donghong Guangxi Minzu Univ Coll Artificial Intelligence Nanning 530006 Peoples R China Chinese Acad Sci State Key Lab Resources & Environm Informat Syst Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China Jiangsu Ctr Collaborat Innovat Geog Informat Resou Nanjing 210023 Peoples R China

Street view images are emerging as new street-level sources of urban environmental information. Accurate detection and quantification of urban air conditioners is crucial for evaluating the resilience of urban residential areas to heat wave disasters and formulating effective disaster prevention policies. Utilizing street view image data to predict the spatial coverage of urban air conditioners offers a simple and effective solution. However, detecting and accurately counting air conditioners in complex street-view environments remains challenging. This study introduced 3D parameter-free attention and coordinate attention modules into the target detection process to enhance the extraction of detailed features of air conditioner external units. It also integrated a small target detection layer to address the challenge of detecting small target objects that are easily missed. As a result, an improved algorithm named SC4-YOLOv7 was developed for detecting and recognizing air conditioner external units in street view images. To validate this new algorithm, we extracted air conditioner external units from street view images of residential buildings in Guilin City, Guangxi Zhuang Autonomous Region, China. The results of the study demonstrated that SC4-YOLOv7 significantly improved the average accuracy of recognizing air conditioner external units in street view images from 87.93% to 91.21% compared to the original YOLOv7 method while maintaining a high speed of image recognition detection. The algorithm has the potential to be extended to various applications requiring small target detection, enabling reliable detection and recognition in real street environments.

关键词： YOLO heat wave hazards street view air conditioner detection algorithm

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Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting

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BMC PUBLIC HEALTH 2021年第1期21卷 1-13页

作者： Bouchouar, Etran Hetman, Benjamin M. Hanley, Brendan Govt Yukon Dept Hlth & Social Serv Whitehorse YT Canada Univ S Florida Coll Publ Hlth Tampa FL 33620 USA Publ Hlth Agcy Canada Canadian Field Epidemiol Program Ottawa ON Canada Univ Guelph Dept Populat Med Guelph ON Canada

BackgroundAutomated Emergency Department syndromic surveillance systems (ED-SyS) are useful tools in routine surveillance activities and during mass gathering events to rapidly detect public health threats. To improve the existing surveillance infrastructure in a lower-resourced rural/remote setting and enhance monitoring during an upcoming mass gathering event, an automated low-cost and low-resources ED-SyS was developed and validated in Yukon, *** of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written using Stata LP 15.1 (Texas, USA) to detect syndromic cases from three different fields (e.g., triage notes;chief complaint;discharge diagnosis), comprising of free-text and standardized codes. Validation was conducted using data from 19,082 visits between October 1, 2018 to April 30, 2019. The National Ambulatory Care Reporting System (NACRS) records were used as a reference for the inclusion of International Classification of Disease, 10th edition (ICD-10) diagnosis codes. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection *** daily secure file transfer of Yukon's Meditech ED-Tracker system data and an aberration detection plan was set up. A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8-89.5% to 62.5-94.1% after implementing improvements identified during validation. As expected, no

关键词： Syndromic surveillance Mass gathering detection algorithm COVID-19 Case definitions

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