Mobile Camera Research Articles

PPCL-RSE: Point prediction for counting and localization of litopenaeus vannamei fry with region-based super-resolution enhancement

Accurate locating and counting of litopenaeus vannamei fry can provide substantial support for vannamei fry sales and scientific feeding. However, traditional methods not only require visual observation by experts, but also are time-consuming and labor-intensive, with no guarantee to reach consensus between salesmen and customers. In contrast, more innovative methods require more expensive equipment or are only effective under specific conditions. The small size and high density nature of the shrimp fry makes its counting even more challenging. In this study, a point prediction method for counting and localization of litopenaeus vannamei fry with region-based super-resolution enhancement (PPCL-RSE) is proposed. Through the inclusion of three modules of density partitioning, high-density region expansion and regional super-resolution, the accuracy of fry counting and locating is improved. The model is deployed on a cloud server for convenient fry counting and localization based on images taken by smartphone cameras. To achieve this, we create a dataset called Vannamei-983 which contains images with more than 1,000,000 fry labeled. The proposed method shows accuracies of 99.04 % and 97.71 % in counting and localization of shrimp fry in low- and high-density images, respectively. The excellent model performance also demonstrate the effectiveness of the strategies considered in the study.

Objective demonstration of eyelid spasm relief with smartphone and custom software in hemifacial spasm patients.

To objectively demonstrate eyelid spasms relief in hemifacial spasm (HFS) patients using a smartphone and a custom-made software. Nineteen patients with HFS had standardized videos recorded with a smartphone (iPhone 6S, Apple) camera before and 15days after receiving onabotulinumtoxinA injections. Nineteen age-matched control subjects were also assessed. The Eye Aspect Ratio (EAR) is an algorithm previously described to determine whether the eye is opened or closed. When the eye is closed, EAR tends to be closer to zero. Analogously, if the eye is wide open, values are greater. A custom-made software using the EAR concept was developed and pre- and post-treatment EARs were analyzed to assess HFS patients. Botulinum toxin (BoNT) injections led to a significant increase inthe average EAR of the affected side: + 10.4% (p = 0.0175) of HFS patients, compared to baseline. MeanEAR before BoNT applications were significantly lower (16.2%) on the affected side (0.25 ± 0.05) of HFS patients when compared to controls (0.30 ± 0.05, p = 0.004). After BoNT injections, no statistically significant difference was observed forthe average EAR between the affected side of HFS patients (0.27 ± 0.04) and controls (p = 0.20). Use of a smartphone and custom-made software objectively demonstrated eyelid spasm relief in patients with HFS. Additional refinement of this system could permit more accurate assessments of treatment response rates for each patient, making it possible to be used in clinical practice.

Rekonstruksi bentuk lambung kapal dalam format tiga dimensi (3D) dengan teknik fotogrametri

Fishing boat has unique characteristics, such as seaworthiness, maneuvering, boat’s velocity, displacement, fishing gear layout, and catch storage facilities. With increasing development of photographic technology, photography is not merely an art but it has become a field of mathematics, making it a technique that can be integrated with software technology designed to produce digital data objects in the form of 3D images called Photogrammetric technique. This study is to obtain the reconstruction of the boat's hull based on the Photogrammetric software, to determine the effect of photography to obtain a 3D image, and to know the weakness and strength of 3D reconstruction of the boat’s hull. The images in this study were obtained using a POCO F3 smartphone camera integrated with the PIX4Dcatch application and analyzed with Agisoft Metashape Professional (Trial Version). From this research, we concluded that 1) the reconstruction of the boat hull can be obtained by using Photogrammetric techniques in the PIX4Dcatch application followed by the Agisoft Metashape Professional (Trial Ver.) software analysis; 2). With photographic equipment and several data processing software, the boat’s shape could be produced in 3D images, and 3). There are several advantages in reconstructing the ship's hull with the Photogrammetric technique, namely producing the ship's reconstruction of 3D images, obtaining the principal dimensions of the boat, such as the area and volume of the boat, that could be as the basic data for boat resistance and ship stability calculation, and the work could be done by one person only.

Patient Comfort with Before and After Photography at Plastic Surgery Offices.

Before and after (B&A) photographs are a sensitive part of patients' medical records, and the use of smartphones may pose risks to confidentiality and comfort. The purpose of this study was to assess patient comfort depending on the circumstances under which these photographs being taken. Amazon's Mechanical Turk crowdsourcing service and REDCap's survey manager were used to recruit survey participants. An anonymous survey was distributed to ascertain demographics and comfort in various B&A scenarios using a five-point Likert scale. T tests and ANOVA testing were used to compare groups. There were 411 respondents with an average age of 36.1 years old. Of them, 46% were female and the majority were White (90%) and non-Hispanic (64%). Nearly one-third had previously undergone plastic surgery, with 80% receiving B&A photography. Surgeons took these photographs 51% of the time with similar rates of smartphone cameras use (47%) versus professional cameras (52%). The public had similar levels of comfort when a nurse or a surgeon took the clinical photographs (p=0.08). Patients were significantly less comfortable when non-medically trained office staff captured their photographs (p=0.0041). The public had similar comfort levels with the use of smartphones and professional cameras when dressed but were significantly less comfortable with the use of a smartphone when unclothed (p=<0.001). To ensure the best patient experience, B&A photography should be taken by a medical professional. If photographs are to be taken when the patient is unclothed, the use of a professional-grade camera may help ease patient discomfort. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The Development of Augmented Reality As English Learning Media in Junior High School

The existence of learning media on various platforms provides variety and assistance for teachers in delivering learning materials. Not much has been developed in educational media compared to entertainment media such as gaming, films, songs, dance, and music. Educational media need to be packaged in a simple, effective, and efficient manner and respond to the needs of today’s students. In the context of the world of learning English at the junior high school level, learning media is needed as an effort to provide real experience in terms of honing English communication skills. Augmented Reality is one of the media that is able to bridge the needs of students, namely making abstract learning experiences feel concrete. Therefore, this research aims to design learning media for junior high school English on the basis of Augmented Reality with content containing stories from North Sumatra. The research method applied in this study is Research &amp; Development. Data acquisition techniques used were documentation, questionnaires, interviews, and tests which were applied in accordance with nine research stages, namely: (1) identification and analysis of media needs; (2) collection of media materials and tools; (3) development of media prototype designs; (4) implementation media prototype; (5) media prototype validation; (6) media prototype revision; (7) media trial on junior high school students; (8) final revision; and (9) media prototype that has been tested. The final result of this study contains AR in the form of flash cards. AR markers are printed on cards and students only focus their smartphone cameras on markers that have been printed in card form. After the camera has successfully scanned the marker, a learning video will appear. There are five cards (markers) in this study, and each card will play a different learning video.&#x0D; Keywords: augmented reality, media, English, junior high school

Recognition of Angry and Happy Facial Expressions with Local Binary Pattern and Support Vector Machine

Looks are a huge sort of nonverbal correspondence for getting a handle on a singular's opinions and sentiments. Look affirmation has various potential applications, including security, tutoring, and prosperity systems. The justification for this assessment is for a look affirmation system using area twofold model and sponsorship vector machine techniques. It is typical that this structure can perceive two kinds of sentiments, to be explicit angry and delighted to get the right assumption. First accumulate fundamental data and assistant data from Kaggle and phone cameras, second preprocessing data with grayscale and resizing, third surface features using Area equal model extraction, fourth assist vector with machining about look request used, finally structure evaluation considering precision, exactness, survey, and F-1 worth. The results show that the look affirmation system works honorably on area matched model and sponsorship vector machine. On this investigation dataset, support vector machine gathering on direct part has favored execution over winding reason ability segment. The most significant precision was achieved with the straight part at 86.25%. This study assumes that the look affirmation structure can work outstandingly with neighborhood matched model and sponsorship vector machine. The straight part shows better execution on this investigation dataset. This assessment can be also advanced by adding more looks, incorporate extraction methods, and plan.

Quantitative Fluorescent Lateral Flow Strip Sensor for Myocardial Infarction Using Purity-Color Upconversion Nanoparticles.

Acute myocardial infarction is a serious cardiovascular disease and poses significant risks to human health. Its early diagnosis and real-time detection are of great importance. Herein, we design a low-cost device that has a high sensitivity of cTnT and cTnI detection. Dual-color upconversion nanoparticles (UCNPs) are prepared as probes, which not only have high-purity red upconversion luminescence (UCL) under 980 or 808 nm excitation but also achieve good temperature sensing. Temperature-dependent multicolor emission excitation is obtained, and the color turns from white to orange and red with increasing temperature. In particular, the maximum SR and SA values based on nonthermally coupled levels are 4.76% K-1 and 8.6% K-1, which are higher than those based on thermally coupled levels. With the UCNPs-based lateral flow strip (LFS), the specific detection of cTnI and cTnT antigens in samples is achieved with a detection limit of 0.001 ng/mL, which is 1 order of magnitude lower than that of their clinical cutoff. The UCNPs-LFS device has a low-cost laser diode and a simplified laser and permits a mobile-phone camera to collect the results, which has an important influence on the field of biomarker sensing.

Mobile phone applications for 3-dimensional scanning and digital anthropometry: a precision comparison with traditional scanners.

The precision of digital anthropometry through 3-dimensional (3D) scanning has been established for relatively large, expensive, non-portable systems. The comparative performance of modern mobile applications is unclear. Forty-six adults (age: 23.3 ± 5.3 y; BMI: 24.4 ± 4.1 kg/m2) were assessed in duplicate using: (1) a mobile phone application capturing two individual 2D images, (2) a mobile phone application capturing serial images collected during a subject's complete rotation, (3) a traditional scanner with a time of flight infrared sensor collecting visual data from a subject being rotated on a mechanical turntable, and (4) a commercial measuring booth with structured light technology using 20 infrared depth sensors positioned in the booth. The absolute and relative technical error of measurement (TEM) and intraclass correlation coefficient (ICC) for each method were established. Averaged across circumferences, the absolute TEM, relative TEM, and ICC were (1) 0.9 cm, 1.5%, and 0.975; (2) 0.5 cm, 0.9%, and 0.986; (3) 0.8 cm, 1.5%, and 0.974; and (4) 0.6 cm, 1.1%, and 0.985. For total body volume, these values were (1) 2.2 L, 3.0%, and 0.978; (2) 0.8 L, 1.1%, and 0.997; (3) 0.7 L, 0.9%, and 0.998; and (4) 0.8 L, 1.1%, and 0.996, with segmental volumes demonstrating higher relative errors. A 3D scanning mobile phone application involving full rotation of subjects in front of a smartphone camera exhibited similar reliability to larger, less portable, more expensive 3D scanners. In contrast, larger errors were observed for a mobile scanning application utilizing two 2D images, although the technical errors were acceptable for some applications.

Non-invasive blood glucose estimation method based on the phase delay between oxy- and deoxyhemoglobin using visible and near-infrared spectroscopy.

Many researchers have attempted to estimate blood glucose levels (BGLs) noninvasively using near-infrared (NIR) spectroscopy. However, the optical absorption change induced by blood glucose is weak in the NIR region and often masked by interference from other components such as water and hemoglobin. Instead of using direct optical absorption by glucose, this study proposes an index calculated from oxy- and deoxyhemoglobin signals that shows a good correlation with BGLs while using conventional visible and NIR spectroscopy. The metabolic index, which is based on tissue oxygen consumption, was derived through analytical methods and further verified and reproduced in a series of glucose challenge experiments. Blood glucose estimation units were prototyped by utilizing commercially available smart devices. Our experimental results showed that the phase delay between the oxy- and deoxyhemoglobin signals in near-infrared spectroscopy correlates with BGL measured by a conventional continuous glucose monitor. The proposed method was also confirmed to work well with visible spectroscopy systems based on smartphone cameras. The proposed method also demonstrated excellent repeatability in results from a total of 19 oral challenge tests. This study demonstrated the feasibility of non-invasive glucose monitoring using existing photoplethysmography sensors for pulse oximeters and smartwatches. Evaluating the proposed method in diabetic or unhealthy individuals may serve to further increase its practicality.

Feasibility of images acquired using smartphone camera for marginal and internal fit of fixed dental prosthesis: comparison and correlation study

This study aimed to measure marginal and internal fit using images captured with both an optical microscope and a smartphone camera, comparing the fit measurement performance of these devices and analyzing their correlation. Working casts (with 10 posterior and 10 anterior teeth) created to fabricate fixed dental prostheses were used. These working casts were scanned using a desktop scanner (E1) to design an interim crown, and the designed interim crown was fabricated using a three-dimensional (3D) printer. Utilizing the silicone replica technique, the fabricated interim crown replicated the fit, which was then captured using both an optical microscope and a smartphone camera. The captured images were used to measure the marginal and internal fit according to the imaging device. Intraclass correlation coefficients (ICC) were used for reliability analysis according to the imaging device. Furthermore, the Wilcoxon signed-rank test was adopted for the comparative evaluation of the marginal and internal fit between the imaging devices (α = 0.05). The measurement results of the marginal and internal fit according to the optical microscope and smartphone camera did exhibit a significant difference (P < 0.05). The ICC between the two devices showed an “excellent” agreement of over 0.9 at all measurement points (P < 0.001). A smartphone camera could be used to obtain images for evaluating the marginal and internal fit.

94 Smartphone integration in anemia detection for small ruminants with Convolutional Neural Networks

Abstract Anemia, often caused by internal parasites like Haemonchus contortus, presents significant health and productivity challenges for small ruminants. The primary goal of this study was to accurately distinguish between healthy and anemic goats using an image classification system focused on eye conjunctiva images. Over 5,000 eye conjunctiva images from 75 goats were collected at Fort Valley State University farms over a 3-mo period using smartphone cameras. These images were randomly divided into training (70%) and testing (30%) datasets, with each group containing five subfolders corresponding to FAMACHA scores of 1, 2, 3, 4, and 5. A Convolutional Neural Network (CNN) algorithm was utilized for image analysis, incorporating data augmentation techniques such as Resize, RandomHorizontalFlip, RandomVerticalFlip, and RandomRotation. The CNN model was built on the Google Colaboratory platform using CUDA 11.2 and the PyTorch machine learning framework, incorporating three ConvNet layers. The model training used the Adam Optimizer with a slower learning rate of 0.001 and a weight decay of 0.0001 to prevent exploding gradient issues, alongside ReLU and the cross-entropy loss function over 1000 epochs. Results demonstrate that the CNN model was highly effective in classifying eye conjunctiva images of goats to detect anemia based on FAMACHA scores.

Microsurgical Practice with Use of Smartphone Camera as the Microscopic Field.

Accessibility of microsurgical equipment is a major barrier to proper training of surgeons before live patient free flap surgery. A technique is presented that uses a smartphone camera as the microscopic field, eliminating the need for an expensive operative microscope for surgical practice. A convenient and cost-effective simulation protocol could reduce the time frame of the microsurgery learning curve. Furthermore, the use of the smartphone video function may allow improved feedback by mentors, improving access and communication between microsurgical teachers and learners. The PocketSuture smartphone stand is a commercially available device that allows the smartphone camera to be used as magnification. The proposed education protocol included suture practice, vessel dissection, and free tissue transfer in nonliving animal models, with vessel anastomosis and patency confirmation performed with a smartphone camera for field magnification. Video of the suturing technique allowed feedback from the mentor. A progressive suturing protocol leading to the ability to perform microsurgical anastomosis on nonliving animal models was developed. The basic costs for the stand, instrument set and suture were less than $500. The PocketSuture smartphone stand can be used for microsurgical training with real-time video for plastic surgery learners with limited access to microscopes and local mentors.

How to Optimize Epidermal Approximation During Wound Suturing Using a Smartphone Camera

How to Optimize Epidermal Approximation During Wound Suturing Using a Smartphone Camera

Facial recognition based on enhanced neural network

Accurate automatic face recognition (FR) has only become a practical goal of biometrics research in recent years. Detection and recognition are the primary steps for identifying faces in this research, and The Viola-Jones algorithm implements to discover faces in images. This paper presents a neural network solution called modify bidirectional associative memory (MBAM). The basic idea is to recognize the image of a human's face, extract the face image, enter it into the MBAM, and identify it. The output ID for the face image from the network should be similar to the ID for the image entered previously in the training phase. The tests have conducted using the suggested model using 100 images. Results show that FR accuracy is 100% for all images used, and the accuracy after adding noise is the proportions that differ between the images used according to the noise ratio. Recognition results for the mobile camera images were more satisfactory than those for the Face94 dataset.

Validity of resting heart rate derived from contact-based smartphone photoplethysmography compared with electrocardiography: a scoping review and checklist for optimal acquisition and reporting.

With the rise of smartphone ownership and increasing evidence to support the suitability of smartphone usage in healthcare, the light source and smartphone camera could be utilized to perform photoplethysmography (PPG) for the assessment of vital signs, such as heart rate (HR). However, until rigorous validity assessment has been conducted, PPG will have limited use in clinical settings. We aimed to conduct a scoping review assessing the validity of resting heart rate (RHR) acquisition from PPG utilizing contact-based smartphone devices. Our four specific objectives of this scoping review were to (1) conduct a systematic search of the published literature concerning contact-based smartphone device-derived PPG, (2) map study characteristics and methodologies, (3) identify if methodological and technological advancements have been made, and (4) provide recommendations for the advancement of the investigative area. ScienceDirect, PubMed and SPORTDiscus were searched for relevant studies between January 1st, 2007, and November 6th, 2022. Filters were applied to ensure only literature written in English were included. Reference lists of included studies were manually searched for additional eligible studies. In total 10 articles were included. Articles varied in terms of methodology including study characteristics, index measurement characteristics, criterion measurement characteristics, and experimental procedure. Additionally, there were variations in reporting details including primary outcome measure and measure of validity. However, all studies reached the same conclusion, with agreement ranging between good to very strong and correlations ranging from r = .98 to 1. Smartphone applications measuring RHR derived from contact-based smartphone PPG appear to agree with gold standard electrocardiography (ECG) in healthy subjects. However, agreement was established under highly controlled conditions. Future research could investigate their validity and consider effective approaches that transfer these methods from laboratory conditions into the "real-world", in both healthy and clinical populations.

Keyboard and Mouse Free Music Controller

Abstract: Human-machine interface (HMI) is a crucial area of research as gestures have the potential to efficiently control and interact with computers. Many applications for hand detection have been created as a result of the pervasive use of built-in cameras in computers, smartphones, and tablets. For the majority of users, however, many of these are not useful. A straightforward concept for a keyboard- and mouse-free music controller is presented in this research. Using MATLAB code that integrates skin detection, area labelling, erosion, dilation, and motion differentiation, a music player controller is developed using the real-time frame tracking feature of a camera. Three hand detection algorithms are created and assessed for maximum performance and accuracy. Real-time hand detection for operating the music player is provided by the algorithm, which is created with efficiency and speed in mind.

Mobile-Based convolutional neural network model for the early identification of banana diseases

This study aimed to deploy a deep learning model in a mobile application for the early identification of Fusarium Wilt and Black Sigatoka in bananas. In this paper, a Convolutional Neural Network (CNN) model for the classification of Black Sigatoka banana disease and Fusarium Wilt disease is assessed. A dataset of 27,360 images of diseased and healthy banana leaves and stalks that were collected from the farms using a mobile phone camera served as the training data for this model. An extra class of 407 images that are not of the banana plant downloaded from the internet was used to help the model detect other images not of the banana plant. The CNN model achieved an accuracy of 91.17 % and was deployed in a mobile application for the classification of the diseases. This study shows that deep learning can be implemented and assist in the early identification of banana diseases. The application could detect images of healthy and diseased banana leaves and stalks and images not of the banana plant with a confidence score of more than 90 % in less than five seconds per image and provide research-based mitigation recommendations.

Towards ultra-low-cost smartphone microscopy.

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here, we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ∼9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ∼5 𝜇m, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we used an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We used the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. RESEARCH HIGHLIGHTS: We propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of ∼5 𝜇m. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.

Enforcement of Asn Discipline Laws Based on The Online Personnel System Application And Its Impact on Performance In The Office of The Lubuk Sikarah District, Solok City

This research examines disciplinary law enforcement through the Online Civil Service System (KEPO), its obstacles and impact on ASN discipline. This type of research is normative juridical supported by empirical juridical. The data used is secondary and primary data. Secondary data was obtained from document studies and primary data was obtained by interviews. The data obtained was analyzed qualitatively, presented in a qualitative descriptive manner. First research results: In general, enforcement of disciplinary law through the KEPO system for ASN at the Kantor Camat Lubuk Sikarah is less effective. Even though discipline has been enforced by reducing or cutting additional employee income in accordance with Solok Mayor Regulation Number 17 of 2022 concerning Providing Additional Income to Regional ASN Employees. Second, the obstacles in enforcing disciplinary law through the KEPO system are: a) the legal factor is still weak: regulating the presence of a 50 meter radius, b) the law enforcement factor is still reluctant, c) the server facility factor is inadequate, d) the community understanding factor ASN in Kantor Camat Lubuk Sikarah regarding KEPO, e) Cultural Factors in the work environment in Lubuk Sikarah District, ASN's culture is reticent. Another finding from the research: there are ASNs who do not yet have an Android cellphone (camera) and a stable internet network. Meanwhile, the impact of implementing or enforcing ASN disciplinary laws on ASN performance in general has relatively increased, although it is still not effective.

An integrated liposome-based microfluidic strategy for rapid colorimetric analysis: A case study of microRNA-21 detection

In this study, a novel integrated liposome-based microfluidic platform combined with a smartphone was designed for the rapid colorimetric detection of microRNA-21 (miRNA-21) in real samples. The flowing surface-functionalized liposomes were first captured by nucleic acid-functionalized Au nanoparticles in the microfluidic chip. In the presence of miRNA-21, the DNA strand modified on the surface of Au nanoparticles hybridized with the target to form double-stranded products and was cleaved by duplex-specific nuclease (DSN) enzyme, causing the liposomes to be re-released. Then, as the liposomes in the colorimetric module were lysed and the “cellular” contents were released, a step-by-step “glucose-glucose oxidase-3,3′,5,5′-tetramethylbenzidine (TMB)” colorimetric reaction process catalyzed by the G-quadruplex/hemin was triggered. The grayscale values were recorded and recognized by the smartphone camera for miRNA-21 analysis. The advantages of the present strategy included the portability of smartphone-based colorimetric assay, the encapsulation and transport of reactants by liposomes and the low solvent usage of microfluidic chip. Under optimal conditions, this assay exhibited a wide linear range from 1 pM to 1 nM (r2 = 0.9981), and the limit of detection of miRNA-21 was as low as 0.27 pM. Moreover, the high specificity of this strategy allowed its successful application to the rapid analysis of miRNA-21 in real blood serum samples of people with type 2 diabetes.