Article
Engineering, Multidisciplinary
Yuanzhao Yang, Qi Jiang, Masood Danish
Summary: A novel video magnification method based on adaptive Laplacian pyramid is proposed to achieve non-contact optical measurements. The method effectively magnifies small signals and reduces blurring and artifacts.
Article
Engineering, Biomedical
Veronica Mattioli, Davide Alinovi, Gianluigi Ferrari, Francesco Pisani, Riccardo Raheli
Summary: In this paper, two video processing techniques are presented for contact-less estimation of the Respiratory Rate (RR) of framed subjects. Motion-related variations in video signals are exploited to identify respiration and estimate the RR over time. The methods rely on motion magnification algorithms to enhance respiration-related movements and perform spatial decomposition and temporal filtering to extract breathing information. The accuracy of the methods is assessed by comparison with reference data, and the phase-based method demonstrates superior performance in RR estimation.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Information Systems
Li Li, Jianfeng Lu, Shanqing Zhang, Linda Mohaisen, Mahmoud Emam
Summary: This paper proposes a frame duplication forgery detection method based on the analysis of textural features in video frames. The method combines GLCM features and statistical features to detect and locate duplicated frames in video sequences. Experimental results show that this method outperforms other state-of-the-art methods.
Article
Construction & Building Technology
Da-You Duan, K. S. C. Kuang, Zuo-Cai Wang, Xiao-Tong Sun
Summary: Vision-based measurement techniques have made significant progress and been widely applied in the field of structural dynamics. They offer full-field measurement capability and the advantages of noncontact measurement techniques. However, there are some limitations that need to be addressed. Video motion magnification is a method that can amplify small structural motions and, when combined with other techniques and filters, can improve measurement accuracy.
STRUCTURAL CONTROL & HEALTH MONITORING
(2023)
Article
Computer Science, Information Systems
Mehmet Sarigul
Summary: Shakes and jitters in video recordings can be eliminated through digital video stabilization using smart algorithms. This process involves camera motion estimation, motion correction, and stable video synthesis. There are different methods in the literature that perform these steps in various ways. Recent advancements in deep learning have introduced learning-based approaches to video stabilization. This paper provides a detailed explanation of video stabilization methods by analyzing and comparing the approaches used from the past to the present.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Juan Alberto Antonio Velazquez, Marcelo Romero Huertas, Roberto Alejo Eleuterio, Everardo Efren Granda Gutierrez, Federico Del Razo Lopez, Erendira Rendon Lara
Summary: This research explores the combination of MDBS and ASM for improving contour-based detection performance of moving pedestrians in a controlled environment. The method performs well in well-illuminated scenes, but its identification performance is slightly affected by reflections, occlusions, or pronounced movement.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Mechanical
Enjian Cai, Yi Zhang
Summary: This paper proposes a novel perspective of phase estimation by utilizing image priors on phase patches. The method learns nonlocal self-similarity (NSS) prior from training images using the patch group based Gaussian Mixture Model (PG-GMM) learning algorithm, and optimizes the phase information using gaussian component selection and weighted sparse coding. The proposed method achieves high-quality magnifications and clearer time domain motion estimates.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Acoustics
F. Cosco, J. Cuenca, W. Desmet, K. Janssens, D. Mundo
Summary: This work discusses the possibility of using phase-based motion magnification as a non-destructive inspection tool for defect detection and identification in vibrating panels. The method is able to magnify small motions happening in a prescribed bandwidth and is particularly suitable for high-resolution full-field optical techniques. A novel phase-based processing pipeline for defect detection is described and preliminary tests are conducted to assess the feasibility and advantages of the methodology.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Computer Science, Information Systems
J. Laurie, N. Higgins, T. Peynot, L. Fawcett, J. Roberts
Summary: The study aimed to determine if motion magnification could improve non-contact respirations monitoring. Results showed a significant reduction in count error and nurses found it easier to make observations from the processed video. Further studies on a larger scale are urgently needed to inform practice.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Ricard Lado-Roige, Marco A. Perez
Summary: The goal of video motion magnification techniques is to amplify small movements in videos that were previously invisible. This has applications in various fields such as biomedicine, deepfake detection, structural modal analysis, and predictive maintenance. However, distinguishing small motions from noise is challenging, especially when magnifying subtle, sub-pixel movements. This work introduces a state-of-the-art model based on the Swin Transformer that offers improved tolerance to noisy inputs and produces higher-quality outputs with less noise, blurriness, and artifacts compared to prior techniques. The improved output image quality enables more precise measurements for applications relying on magnified video sequences and may facilitate further advancements in video motion magnification techniques in new technical fields.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Software Engineering
Ahmed Mohamed Ahmed, Mohamed Abdelrazek, Sunil Aryal, Thanh Thi Nguyen
Summary: This paper provides an overview of the powerful Eulerian motion magnification techniques, including technical concepts, a comparison between Eulerian and Lagrangian perspectives, and implementation results.
COMPUTERS & GRAPHICS-UK
(2023)
Article
Computer Science, Software Engineering
Rimjhim Padam Singh, Poonam Sharma
Summary: This study proposes a memory-efficient unique combination of multi-color feature space with a lightweight intensity-based texture descriptor for motion recognition in challenging real-world scenarios. The proposed feature space and model have been evaluated on the whole 2014 Change Detection dataset, showing superior performance and memory analysis results.
Article
Acoustics
Qiankun Zhu, Depeng Cui, Qiong Zhang, Yongfeng Du
Summary: Vibration-based structural health monitoring (SHM) systems are useful for assessing structural safety performance. This study presents a noncontact approach using digital cameras to capture structural vibration information and a novel image preprocessing technique to enhance the quality of the signals. The system uses phase-based optical flow estimation, mode decomposition, and phase-based motion magnification to recognize the vibration of the structure.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Computer Science, Information Systems
Hitesh D. Panchal, Hitesh B. Shah
Summary: This paper proposes a three-step frame deletion detection method to detect single and multiple forgeries in videos. The method separates input videos into static and dynamic categories using a key frame extraction algorithm, selects different sets of video quality assessment attributes for static and dynamic videos, and applies multiple linear regression to detect outliers. Experimental results show that the proposed algorithm performs better in detecting frame deletion forgery.
MULTIMEDIA SYSTEMS
(2023)
Article
Automation & Control Systems
Manikandaprabu Nallasivam, Vijayachitra Senniappan
Summary: A new method for moving human target detection and tracking is proposed in this paper, which combines background subtraction and frame subtraction to select moving targets, followed by target tracking using the CAMShift algorithm. The experimental results show superior performance under different lighting conditions and reduced time complexity.
STUDIES IN INFORMATICS AND CONTROL
(2021)
Article
Engineering, Biomedical
Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl
Summary: This study utilized a digital camera to remotely monitor the heart rate and respiratory rate of infants in a clinical setting, showing strong correlation and low error rates compared to reference data. The findings suggest the potential of video camera imaging to replace traditional monitoring in NICU and other contexts.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
(2023)
Article
Chemistry, Multidisciplinary
Ammar Yahya Daeef, Ali Al-Naji, Ali K. Nahar, Javaan Chahl
Summary: Malware is a significant threat to modern businesses, and it is crucial to eliminate it from computer systems. A lightweight solution using artificial intelligence at the edge of the IT system is the most responsive option. This study used visualization analysis and Jaccard similarity to uncover patterns in API calls for high malware detection rates and quick execution. The results showed that random forest (RF) performed similarly to long short-term memory (LSTM) and deep graph convolutional neural networks (DGCNNs), indicating potential for real-time inference on edge devices.
APPLIED SCIENCES-BASEL
(2023)
Article
Remote Sensing
Samuel Teague, Javaan Chahl
Summary: Strapdown celestial imaging sensors offer a compact, lightweight alternative to gimbaled sensors, but they suffer from motion blur due to a wider field of view. This study presents a method to extract star trails and correct noisy inertial attitude measurements using least squares approach. Synthetic and real image data demonstrate the effectiveness of the proposed method. The findings indicate that strapdown celestial imagery with motion blur can achieve accurate attitude estimation on lightweight UAV hardware.
Article
Energy & Fuels
Stephen Lucas, Romeo Marian, Michael Lucas, Titilayo Ogunwa, Javaan Chahl
Summary: Electrical insulation failure is the most common failure mechanism in electrical machines, driven by high temperatures and temperature gradients. This paper examines the effectiveness of using thermoelectric coolers (TECs) to heat the inner core or winding area of a motor, demonstrating the successful integration of TECs into a motor. The results show that TECs effectively pump heat into the core, keeping the winding hot and eliminating condensation issues and water ingress.
Article
Energy & Fuels
Stephen Lucas, Romeo Marian, Michael Lucas, Titilayo Ogunwa, Javaan Chahl
Summary: Electric motors and generators are crucial to the modern world, consuming approximately 45% of the world's energy. This paper explores the use of thermoelectric coolers/heaters to improve the thermal management of electrical machines. By maintaining internal heat and reducing moisture ingress, these solid-state devices help create a more thermally stable environment, resulting in longer operational life and reduced costs.
Article
Automation & Control Systems
Ziyue Jin, Romeo M. Marian, Javaan S. Chahl
Summary: The manufacturing industry is facing challenges due to changing customer demands, which require manufacturers to be more flexible and adaptive. This paper presents the concept of batch-size-of-one production, a fully automated and highly customized production model with short lead times. The proposed model is a promising solution for manufacturing challenges, especially for highly customized or similar products like in the mobile phone industry. In addition, a novel control method is introduced to enable industrial robots to operate in the desired batch-size-of-one production model without the need for reconfiguration and reprogramming. The aim is to create a fully automated robot assembly cell with minimal human involvement by eliminating interruptions from reconfiguration and reprogramming processes.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Robotics
Tran Xuan Bach Nguyen, Kent Rosser, Asanka Perera, Philip Moss, Javaan Chahl
Summary: The study investigates the feasibility of using optical flow-based neural networks on real-world thermal aerial imagery. Traditional optical flow techniques have shown adequate performance, but their efficacy is limited in low-contrast conditions. Convolutional neural networks have demonstrated good performance with strong generalization. The deep-learning network outperformed established sparse and dense optical flow techniques in various environments and weather conditions, but at the cost of higher computational demand.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Chemistry, Multidisciplinary
Yiting Tao, Michael Lucas, Asanka Perera, Samuel Teague, Eric Warrant, Javaan Chahl
Summary: In this study, we examined the feasibility of utilizing the Milky Way for maintaining heading in machine vision systems on autonomous vehicles. By measuring its visual features and characteristics, and considering the conditions and sensory systems used by insects, we demonstrated that computer vision methods can accurately extract the Milky Way's orientation. However, higher levels of light pollution can negatively impact navigation systems relying on the Milky Way.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Aerospace
Blake McIvor, John McGuire, Javaan Chahl
Summary: We propose a method for generating feedback and controlling multi-coil linear electromagnetic actuators for flapping wing systems. By using 3D-printed structures and miniaturised electromagnetic actuators, we have constructed a self-lifting system with a combined weight of 3.07 g. Combining multiple magnets and coils into a single actuator with onboard feedback sensors has significantly improved power densities compared to existing linear electromagnetic systems.
Review
Computer Science, Interdisciplinary Applications
Saja Theab Ahmed, Dalal Abdulmohsin Hammood, Raad Farhood Chisab, Ali Al-Naji, Javaan Chahl
Summary: In medical information systems, image data plays a crucial role and its protection is essential. Encryption methods for digital images are important for ensuring security and authenticity, particularly with the increasing use of telemedicine and online sharing of medical images. The attention given to medical image encryption reflects concerns about the safety of medical communication.
Article
Engineering, Biomedical
Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. G. Perera, Danyi Wang, Javaan Chahl
Summary: The study proposes a non-invasive neonatal jaundice detection system based on skin colour analysis and machine learning. It automatically selects a region of interest from an infant image and analyzes its colour to classify jaundice or normal. The system has the potential for clinical application.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
(2023)
Article
Engineering, Multidisciplinary
Rusul Sabah Jebur, Mohd Hazli Bin Mohamed Zabil, Dalal Abdulmohsin Hammood, Lim Kok Cheng, Ali Al-Naji
Summary: This study proposes a novel approach that combines deep hybrid learning with the Self-Improved Orca Predation Algorithm (SI-OPA) for image denoising. Extensive comparisons against state-of-the-art denoising methods are conducted, demonstrating the superior performance of the proposed approach in terms of denoising effectiveness, computational efficiency, and preservation of image details. Implemented in Python, the hybrid model showcases the benefits of combining Bi-LSTM, optimized CNN, and SI-OPA for advanced image-denoising applications.
Article
Psychology, Mathematical
Danyi Wang, Johanna Eckert, Sam Teague, Ali Al-Naji, Daniel Haun, Javaan Chahl
Summary: Cardiac measures, such as heart rate measurements, are crucial for assessing both physiological and psychological states. However, their use is limited in comparative psychology due to the traditional methods requiring sensor attachment, usually only feasible during anesthesia or after extensive training for nonhuman primates. This study introduces a camera-based contact-free system that accurately detects and estimates the heart rates of unrestrained chimpanzees, allowing for new avenues of research and improved health management of captive individuals.
BEHAVIOR RESEARCH METHODS
(2023)
Article
Engineering, Biomedical
Wenwen Wu, Yanqi Huang, Xiaomei Wu
Summary: In this study, a 2D deep learning classification network SRT was proposed to improve automatic ECG analysis. The model structure was enhanced with the CNN and Transformer-encoder modules, and a novel attention module and Dilated Stem structure were introduced to improve feature extraction. Comparative experiments showed that the proposed model outperformed several advanced methods.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Chiheb Jamazi, Ghaith Manita, Amit Chhabra, Houssem Manita, Ouajdi Korbaa
Summary: In this study, a new dynamic and intelligent clustering method for brain tumor segmentation is proposed by combining the improved Aquila Optimizer (AO) and the K-Means algorithm. The proposed MAO-Kmeans approach aims to automatically extract the correct number and location of cluster centers and the number of pixels in each cluster in abnormal MRI images, and the experimental results demonstrate its effectiveness in improving the performance of conventional K-means clustering.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Alberto Hernando, Maria Dolores Pelaez-Coca, Eduardo Gil
Summary: This study applied a new algorithm to decompose the photoplethysmogram (PPG) pulse and identified changes in PPG pulse morphology due to pressure. The results showed that there was an increase in amplitude, width, and area values of the PPG pulse, and a decrease in ratios when pressure increased, indicating vasoconstriction. Furthermore, some parameters were found to be related to the pulse-to-pulse interval.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Jens Moeller, Eveline Popanda, Nuri H. Aydin, Hubert Welp, Iris Tischoff, Carsten Brenner, Kirsten Schmieder, Martin R. Hofmann, Dorothea Miller
Summary: In this study, a method based on texture features is proposed, which can classify healthy gray and white matter against glioma degrees 4 samples with reasonable classification performance using a relatively low number of samples for training. The method achieves high classification performance without the need for large datasets and complex machine learning approaches.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Amrutha Bhaskaran, Manish Arora
Summary: The study evaluates a cyclic repetition frequency-based algorithm for fetal heart rate estimation. The algorithm improves accuracy and reliability for poor-quality signals and performs well for different gestation weeks and clinical settings.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Manan Patel, Harsh Bhatt, Manushi Munshi, Shivani Pandya, Swati Jain, Priyank Thakkar, Sangwon Yoon
Summary: Electroencephalogram (EEG) signals have been effectively used to measure and analyze neurological data and brain-related ailments. Artificial Intelligence (AI) algorithms, specifically the proposed CNN-FEBAC framework, show promising results in studying the EEG signals of autistic patients and predicting their response to stimuli with 91% accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Wencheng Gu, Kexue Sun
Summary: This research proposes an improved version of YOLOv5 (AYOLOv5) based on the attention mechanism to address the issue of low recognition rate in cell detection. Experimental results demonstrate that AYOLOv5 can accurately identify cell targets and improve the quality and recognition performance of cell pictures.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Anita Gade, V. Vijaya Baskar, John Panneerselvam
Summary: Analysis of exhaled breath is an increasingly used diagnostic technique in medicine. This study introduces a new NICBGM-based model that utilizes various features and weight optimization for accurate data interpretation and result optimization.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Arsalan Asemi, Keivan Maghooli, Fereidoun Nowshiravan Rahatabad, Hamid Azadeh
Summary: Biometric authentication systems can perform identity verification with optimal accuracy in various environments and emotional changes, while the performance of signature verification systems can be affected when people are under stress. This study examines the performance of a signature verification system based on muscle synergy patterns as biometric characteristics for stressed individuals. EMG signals from hand and arm muscles were recorded and muscle synergies were extracted using Non-Negative Matrix Factorization. The extracted patterns were classified using Support Vector Machine for authentication of stressed individuals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tianjiao Guo, Jie Yang, Qi Yu
Summary: This paper proposes a CNN-based approach for segmenting four typical DR lesions simultaneously, achieving competitive performance. This approach is significant for DR lesion segmentation and has potential in other segmentation tasks.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
G. Akilandasowmya, G. Nirmaladevi, S. U. Suganthi, A. Aishwariya
Summary: This study proposes a technique for skin cancer detection and classification using deep hidden features and ensemble classifiers. By optimizing features to reduce data dimensionality and combining ensemble classifiers, the proposed method outperforms in skin cancer classification and improves prediction accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tuuli Uudeberg, Juri Belikov, Laura Paeske, Hiie Hinrikus, Innar Liiv, Maie Bachmann
Summary: This article introduces a novel feature extraction method, the in-phase matrix profile (pMP), specifically adapted for electroencephalographic (EEG) signals, for detecting major depressive disorder (MDD). The results show that pMP outperforms Higuchi's fractal dimension (HFD) in detecting MDD, making it a promising method for future studies and potential clinical use for diagnosing MDD.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
P. Nancy, M. Parameswari, J. Sathya Priya
Summary: Stroke is the third leading cause of mortality worldwide, and early detection is crucial to avoid health risks. Existing research on disease detection using machine learning techniques has limitations, so a new stroke detection system is proposed. The experimental results show that the proposed method achieves a high accuracy rate in stroke detection.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Shimin Liu, Zhiwen Huang, Jianmin Zhu, Baolin Liu, Panyu Zhou
Summary: In this study, a continuous blood pressure (BP) monitoring method based on random forest feature selection (RFFS) and a gray wolf optimization-gradient boosting regression tree (GWO-GBRT) prediction model was developed. The method extracted features from electrocardiogram (ECG) and photoplethysmography (PPG) signals, and employed RFFS to select sensitive features highly correlated with BP. A hybrid prediction model of gray wolf optimization (GWO) technique and gradient boosting regression tree (GBRT) algorithm was established to learn the relationship between BP and sensitive features. Experimental results demonstrated the effectiveness and advancement of the proposed method.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Weijun Gong, Yurong Qian, Weihang Zhou, Hongyong Leng
Summary: The recognition of dynamic facial expressions is challenging due to various factors, and obtaining discriminative expression features has been difficult. Traditional deep learning networks lack understanding of global and temporal expressions. This study proposes an enhanced spatial-temporal learning network to improve dynamic facial expression recognition.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
