Engineering Commons^™

Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia

Research outputs 2022 to 2026

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …

High-Throughput Phenotyping Of Plant Leaf Morphological, Physiological, And Biochemical Traits On Multiple Scales Using Optical Sensing, Huichun Zhang, Lu Wang, Xiuliang Jin, Liming Bian, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth, health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, …

Application Of Image Processing In Soil Mechanics, Luke Knodel

Senior Honors Theses

Whenever someone digs a hole in the ground or takes a relaxing walk on the beach, they directly interact with the soil. In its basic form, soil consists of solid, water, and air phases. Unlike water and metals, soil is a particulate media, and the relative proportion of the individual phases significantly influences its physical properties. Various studies have analyzed soil using image processing to determine its morphological properties. Research involving the digital processing of X-ray Computed Tomography (X-ray CT) images of soil to retrieve physically meaningful information is gaining recognition. This study investigates two-dimensional X-ray CT images of unsaturated …

Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …

Advances And Applications Of Dsmt For Information Fusion. Collected Works, Volume 5, Florentin Smarandache, Jean Dezert, Albena Tchamova

Branch Mathematics and Statistics Faculty and Staff Publications

This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 (available at fs.unm.edu/DSmT-book4.pdf or www.onera.fr/sites/default/files/297/2015-DSmT-Book4.pdf) in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.

First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of …

Canopycam – An Edge-Computing Sensing Unit For Continuous Measurement Of Canopy Cover Percentage Of Dry Edible Beans, Wei-Zhen Liang, Joseph Oboamah, Xin Qiao, Yufeng Ge, Robert M. Harveson, Daran Rudnick, Jun Wang, Haishun Yang, Angie Gradiz

Department of Biological Systems Engineering: Papers and Publications

Canopy cover (CC) is an important indicator for crop development. Currently, CC can be estimated indirectly by measuring leaf area index (LAI) using commercially available hand-held meters. However, it does not capture the dynamics of CC. Continuous CC monitoring is essential for dry edible beans production since it can affect crop water use, weed, and disease control. It also helps growers to closely monitor “yellowness”, or senescence of dry beans to decide proper irrigation cutoff timing to allow the crop to dry down for harvest. Therefore, the goal of this study was to develop a device – CanopyCAM, containing software …

Development An Edge-Computing Sensing Unit For Continuous Measurement Of Canopy Cover Percentage Of Dry Edible Beans, Wei-Zhen Liang, Joseph Oboamah, Xin Qiao, Yufeng Ge, Robert M. Harveson, Daran R. Rudnick, Jun Wang, Haishun Yang, Angie Gradiz

Department of Biological Systems Engineering: Papers and Publications

Canopy cover (CC) is an important indicator for crop development. Currently, CC can be estimated indirectly by measuring leaf area index (LAI), using commercially available hand-held meters. However, it does not capture the dynamics of CC. Continuous CC monitoring is essential for dry edible beans production since it can affect crop water use, weed, and disease control. It also helps growers to closely monitor “yellowness”, or senescence of dry beans to decide proper irrigation cutoff to allow the crop to dry down for harvest. The goal of this study was to develop a device – CanopyCAM, containing software and hardware …

The Dark Annulus Of A Drop In A Hele-Shaw Cell Is Caused By The Refraction Of Light Through Its Meniscus, Sangjin Ryu, Haipeng Zhang, Carson Emeigh

Department of Mechanical and Materials Engineering: Faculty Publications

Knowing the meniscus shape of confined drops is important for understanding how they make first contact and then coalesce. When imaged from the top view by brightfield microscopy, a liquid drop (e.g., corn syrup) confined in a Hele-Shaw cell, surrounded by immiscible liquid (e.g., mineral oil), had a dark annulus, and the width of the annulus decreased with increasing concentration of corn syrup. Since the difference in the annulus width was presumed to be related to the meniscus shape of the drops, three-dimensional images of the drops with different concentrations were obtained using confocal fluorescence microscopy, and their cross-sectional meniscus …

Investigating 3d-Printability Of A Maine-Based Bio-Ink, Jordyn Judkins

Honors College

Biofabrication is the process of creating complex biologic products, such as artificial tissues, from raw materials such as living cells, biomaterials, and molecules. This can be done using 3D printed bio-ink, which is a combination of biomaterials and cells. However, the bio-ink must be a shear thinning fluid to allow for high-resolution and continuous printing, but also demonstrate post-printing mechanical integrity to self- support the structure, which is challenging to achieve. The research conducted here investigates how to improve the mechanical functionality of bio-ink using additives available in Maine. Chitosan, sodium alginate, and TEMPO nano fibrillated cellulose were chosen as …

Image Provenance Analysis, Daniel Moreira, William Theisen, Walter Scheirer, Aparna Bharati, Joel Brogan, Anderson Rocha

Computer Science: Faculty Publications and Other Works

The literature of multimedia forensics is mainly dedicated to the analysis of single assets (such as sole image or video files), aiming at individually assessing their authenticity. Different from this, image provenance analysis is devoted to the joint examination of multiple assets, intending to ascertain their history of edits, by evaluating pairwise relationships. Each relationship, thus, expresses the probability of one asset giving rise to the other, through either global or local operations, such as data compression, resizing, color-space modifications, content blurring, and content splicing. The principled combination of these relationships unveils the provenance of the assets, also constituting an …

Novel Damage Index-Based Rapid Evaluation Of Civil Infrastructure Subsurface Defects Using Thermography Analytics, Tianjie Zhang, Md Asif Rahman, Alex Peterson, Yang Lu

Civil Engineering Faculty Publications and Presentations

The qualitative measurement is a common practice in infrastructure condition inspection when using Infrared Thermography (IRT), as it can effectively locate the defected area non-destructively and non-contact. However, a quantitative evaluation becomes more significant because it can help decision makers figure out specific compensation plans to deal with defects. In this work, an IRT-based novel damage index, damage density, was proposed to quantify the significance of subsurface defects. This index is extracted from IR images using our thermography analytics framework. The proposed framework includes thermal image processing, defect edge detection, and thermal gradient map calculations. A modified root mean square …

Reference-Free Differential Histogram-Correlative Detection Of Steganography: Performance Analysis, Natiq M. Abdali, Zahir M. Hussain

Research outputs 2022 to 2026

Recent research has demonstrated the effectiveness of utilizing neural networks for detect tampering in images. However, because accessing a database is complex, which is needed in the classification process to detect tampering, reference-free steganalysis attracted attention. In recent work, an approach for least significant bit (LSB) steganalysis has been presented based on analyzing the derivatives of the histogram correlation. In this paper, we further examine this strategy for other steganographic methods. Detecting image tampering in the spatial domain, such as image steganography. It is found that the above approach could be applied successfully to other kinds of steganography with different …

Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo

Department of Information Systems & Computer Science Faculty Publications

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, …

Characterization Of Tea (Camellia Sinensis) Granules For Quality Grading Using Computer Vision System, Md Towfiqur Rahman, Sabiha Ferdous, Mariya Sultana Jenin, Tanjina Rahman Mim, Masud Alam, Muhammad Rashed Al Mamun

Department of Biological Systems Engineering: Papers and Publications

Tea (Camellia sinensis) has been found as an important medicinal beverage for human which is consumed all over the world. Primarily, the majority of tea is being cultivated in Asia and Africa, however it is commercially produced by more than 60 countries. Though substantial amount is produced, its processing system is still underdeveloped which leads to decrease in export opportunity as well as low monetary value. Moreover, the traditional method of tea grading and sorting is laborious, inefficient, and costly which ultimately produces the low-quality heterogeneous products. Processing and grading of tea granules after drying is very important …

Efficient, Low-Cost Bridge Cracking Detection And Quantification Using Deep-Learning And Uav Images, Chao Sun, Xiangyu Meng, Joshua O. Ogbebor, Shaopan Guo

Publications

Many bridges in the State of Louisiana and the United States are working under serious degradation conditions where cracks on bridges threaten structural integrity and public security. To ensure structural integrity and public security, it is required that bridges in the US be inspected and rated every two years. Currently, this biannual assessment is largely implemented using manual visual inspection methods, which is slow and costly. In addition, it is challenging for workers to detect cracks in regions that are hard to reach, e.g., the top part of the bridge tower, cables, mid-span of the bridge girders, and decks. This …

Contact Angle Measurement Using A Hele-Shaw Cell: A Proof-Of-Concept Study, Haipeng Zhang, Jacob Gottberg, Sangjin Ryu

Department of Mechanical and Materials Engineering: Faculty Publications

Contact angle is an important property to quantify the wettability of a solid surface with a liquid, which characterizes interactions of the solid-liquid pair. Generally, to measure contact angle, special instruments such as a goniometer are necessary, but they are not readily available in certain research settings. In this study, an alternative method to measure contact angle based on a Hele-Shaw cell, microscopy imaging, and image processing is suggested. In this method, a liquid drop is injected into a transparent Hele-Shaw cell, the meniscus of the drop is captured in the top or bottom view using a brightfield microscope, and …

Bibliometric Survey On Image Processing Techniques Using Lattice Boltzmann Method For Cfd Simulations, Priyambada Praharaj Mrs, Chandrakant Sonawane Dr, Madhura Ingalhalikar Dr

Library Philosophy and Practice (e-journal)

This bibliometric analysis aims to understand how Lattice Boltzmann Method could be a potential solver in integrating computational fluid dynamics with image segmentation smoothly. Cardiovascular diseases have been a major health problem in our society and have been an interesting topic for researchers to focus on. Computational Fluid dynamics (CFD) simulation on well-segmented patient-specific images could help the clinicians in diagnosing many cardiovascular diseases in the initial stages itself thereby avoiding surgery. This paper focuses on how various methods have been used since 1988 and been successfully implemented in subsequent years. The bibliometric analysis is done from Scopus and the …

Bibliometric Review On Image Based Plant Phenotyping, Shrikrishna Ulhas Kolhar, Jayant Jagtap

Library Philosophy and Practice (e-journal)

Plant phenotyping is a quantitative description of structural, physiological and temporal traits of plants resulting from interaction of plant genotypes with the environment. A rapid development is in progress in the field of image-based plant phenotyping. Plant phenotyping has wide range of applications in plant breeding research, plant growth prediction, biotic and abiotic stress analysis, crop management and early disease detection. The main motive is to provide detailed bibliometric review in order to know the available literature and current research trends in the area of plant phenotyping using plant images. The bibliometric analysis is primarily based on Scopus, web of …

Measurement Of Micro Burr And Slot Widths Through Image Processing: Comparison Of Manual And Automated Measurements In Micro‐Milling, Fatih Akkoyun, Ali Ercetin, Kubilay Aslantas, Danil Yurievich Pimenov, Khaled Giasin, Avinash Lakshmikanthan, Muhammad Aamir

Research outputs 2014 to 2021

In this study, the burr and slot widths formed after the micro‐milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user‐defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured …

Anatomical Fraction Segmentation In The Biomass Bales, Rahul Reddy Kancharla, William A. Smith, Elisa H. Barney Smith, Jordan L. Klinger

Electrical and Computer Engineering Faculty Publications and Presentations

According to the Bioenergy Technologies Office (BETO), creating a robust next-generation domestic bioenergy industry is an essential pathway for providing sustainable renewable energy alternatives. Using non-food feedstocks, like corn-stover and forest residue, in the biorefineries doesn't affect the food supply chain. In the commercial-scale bioenergy operations, a significant development in the technological advancements is required to determine the biomass feedstock quality at the preprocessing stage. The penetrating ability of the x-rays helps study the big biomass bales, but the feedstock heterogeneity—physical size, shape, and chemical composition—poses a significant challenge during milling, conveyance, feeding, and biofuel conversion processes. The inherent complexity …

Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell

Research Collection School Of Computing and Information Systems

Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation …

Machine Learning And Image Processing For Noise Removal And Robust Edge Detection In The Presence Of Mixed Noise, Mehdi Mafi

FIU Electronic Theses and Dissertations

The central goal of this dissertation is to design and model a smoothing filter based on the random single and mixed noise distribution that would attenuate the effect of noise while preserving edge details. Only then could robust, integrated and resilient edge detection methods be deployed to overcome the ubiquitous presence of random noise in images. Random noise effects are modeled as those that could emanate from impulse noise, Gaussian noise and speckle noise.

In the first step, evaluation of methods is performed based on an exhaustive review on the different types of denoising methods which focus on impulse noise, …

System And Method For Radio Tomographic Image Formation, Richard K. Martin

AFIT Patents

A system and method for generating radio tomographic images is provided. A plurality of transceivers positioned around a region to be imaged is divided into a plurality of pixels. A control apparatus is configured to cause each of the plurality of transceivers in turn to send a signal to each of the other transceivers. The control apparatus is further configured to determine an attenuation in the received signals, generate weighing, derivative, and attenuation matrices from the signals, group the pixels into a plurality of provinces, select each province in turn and solve for a change in attenuation in each of …

Erratum: "Imaging The Three‐Dimensional Orientation And Rotational Mobility Of Fluorescent Emitters Using The Tri‐Spot Point Spread Function", Oumeng Zhang, Jin Lu, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

In the original paper, a calibration error exists in the image-formation model used to analyze experimental images taken by our microscope, causing a bias in the orientation measurements in Figs. 2 and 3. The updated measurements are shown in Fig. E1. We have also updated the supplementary material for the original article to discuss the revised PSF model and estimation algorithms (supplementary material 2) and show the revised model and measurements (Figs. S1, S3, S7, S8, and S10–S13).

A Multi-Sensor Phenotyping System: Applications On Wheat Height Estimation And Soybean Trait Early Prediction, Wenan Yuan

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

Phenotyping is an essential aspect for plant breeding research since it is the foundation of the plant selection process. Traditional plant phenotyping methods such as measuring and recording plant traits manually can be inefficient, laborious and prone to error. With the help of modern sensing technologies, high-throughput field phenotyping is becoming popular recently due to its ability of sensing various crop traits non-destructively with high efficiency. A multi-sensor phenotyping system equipped with red-green-blue (RGB) cameras, radiometers, ultrasonic sensors, spectrometers, a global positioning system (GPS) receiver, a pyranometer, a temperature and relative humidity probe and a light detection and ranging (LiDAR) …

In Vivo Human-Like Robotic Phenotyping Of Leaf And Stem Traits In Maize And Sorghum In Greenhouse, Abbas Atefi

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

In plant phenotyping, the measurement of morphological, physiological and chemical traits of leaves and stems is needed to investigate and monitor the condition of plants. The manual measurement of these properties is time consuming, tedious, error prone, and laborious. The use of robots is a new approach to accomplish such endeavors, which enables automatic monitoring with minimal human intervention. In this study, two plant phenotyping robotic systems were developed to realize automated measurement of plant leaf properties and stem diameter which could reduce the tediousness of data collection compare to manual measurements. The robotic systems comprised of a four degree …

Low-Energy Acceleration Of Binarized Convolutional Neural Networks Using A Spin Hall Effect Based Logic-In-Memory Architecture, Ashkan Samiee, Payal Borulkar, Ronald F. Demara, Peiyi Zhao, Yu Bai

Engineering Faculty Articles and Research

Deep Learning (DL) offers the advantages of high accuracy performance at tasks such as image recognition, learning of complex intelligent behaviors, and large-scale information retrieval problems such as intelligent web search. To attain the benefits of DL, the high computational and energy-consumption demands imposed by the underlying processing, interconnect, and memory devices on which software-based DL executes can benefit substantially from innovative hardware implementations. Logic-in-Memory (LIM) architectures offer potential approaches to attaining such throughput goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we develop a Spintronic Logic-in-Memory (S-LIM) XNOR neural …

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …

Multi-Pig Part Detection And Association With A Fully-Convolutional Network, Eric T. Psota, Mateusz Mittek, Lance C. Pérez, Ty Schmidt, Benny Mote

Department of Electrical and Computer Engineering: Faculty Publications

Computer vision systems have the potential to provide automated, non-invasive monitoring of livestock animals, however, the lack of public datasets with well-defined targets and evaluation metrics presents a significant challenge for researchers. Consequently, existing solutions often focus on achieving task-specific objectives using relatively small, private datasets. This work introduces a new dataset and method for instance-level detection of multiple pigs in group-housed environments. The method uses a single fully-convolutional neural network to detect the location and orientation of each animal, where both body part locations and pairwise associations are represented in the image space. Accompanying this method is a new …