Digital Photographic Camera Research Articles

Цифровой сглаживающий трапецеидальный рекурсивно-сепарабельный фильтр обработки изображений с изменяемыми размерами сканирующей многоэлементной апертуры

The development of television systems is an important factor for many industries involved in the acquisition, processing, storage and transmission of images. Today, an urgent task in the use of such systems is to improve the quality of images obtained using digital photo and video cameras. To solve this problem, digital recursive-separable smoothing filters can be used. The paper describes the process of operation of the algorithm for changing the size of the scanning multi-element aperture of a smoothing trapezoidal recursive-separable filter for digital image processing. The results of evaluating its performance relative to the same algorithm implemented through classical two-dimensional convolution for various sizes of test images are presented. The influence of the aperture size of the developed filter on the change in the signal-to-noise ratio is assessed. The algorithm is implemented in the MATLAB computing environment.

Hue-Preserving Color Transforms for LED Wall Virtual Production Workflows

Virtual production using light-emitting diode (LED) wall display technology is gaining popularity in the entertainment industry to produce motion pictures, episodic television, live broadcast, and esports content. This new paradigm typically uses one or more large LED displays that contain millions of individual LEDs that are used to display a virtual background and/or foreground objects from a virtual scene that is simultaneously captured by the digital photographic camera on set, resulting in the so-called “in-camera visual effects.” In a virtual production workflow, digital cameras capture the actors and objects on the set in the foreground while simultaneously capturing the image shown on the LED wall behind the actors. Realtime video game rendering engines update the image shown on the LED wall to compensate for changes in camera location, camera pose, and lens focal length. Modern digital camera workflows typically include color transforms that were not designed to accurately render the large areas of saturated colors that are possible when capturing the image shown on an LED wall. Some examples of a hue shift that can occur in typical workflows are blue to cyan, red to pink, red to orange, and green to yellow. We found that these hue shifts can occur dynamically while racking focus to and from the LED wall and also statically when the LED wall is kept out of focus, which is a common technique that is used to minimize moiré artifacts. This article explores a simple modification of these common color transforms to preserve the hue of the scene while also creating a similar look to the existing color transforms.

Data on 824 fireballs observed by the digital cameras of the European Fireball Network in 2017–2018

A catalog of 824 fireballs (bright meteors), observed by a dedicated network of all-sky digital photographic cameras in central Europe in the years 2017–2018 is presented. The status of the European Fireball Network, established in 1963, is described. The cameras collect digital images of meteors brighter than an absolute magnitude of about −2 and radiometric light curves with a high temporal resolution of those brighter than a magnitude ≈−4. All meteoroids larger than 5 g, corresponding to sizes of about 2 cm, are detected regardless of their entry velocity. High-velocity meteoroids are detected down to masses of about 0.1 g. The largest observed meteoroid in the reported period 2017–2018 had a mass of about 100 kg and a size of about 40 cm. The methods of data analysis are explained and all catalog entries are described in detail. The provided data include the fireball date and time, atmospheric trajectory and velocity, the radiant in various coordinate systems, heliocentric orbital elements, maximum brightness, radiated energy, initial and terminal masses, maximum encountered dynamic pressure, physical classification, and possible shower membership. Basic information on the fireball spectrum is available for some bright fireballs (apparent magnitude <−7). A simple statistical evaluation of the whole sample is provided. The scientific analysis is presented in an accompanying paper.

Определение смещений поверхности ледника по разновременным данным с беспилотных воздушных судов

The shelf and outlet glaciers fluctuation characteristics are classically performed by comparing multi-temporal mapping sources, geophysical and remote sensing methods. The unmanned aerial vehicles (UAVs) usage equipped with GNSS receivers and digital photographic cameras enables obtaining georeferenced information and images. This data can be successfully employed for characterizing the movement of the glacier. The author proposes a modified pseudo-parallax method, which uses the multi-temporal survey materials obtained from the UAVs to determine the spatial displacements of the glacier surface. Its efficiency is demonstrated on the movement pattern determination example of the Dålk Glacier (North Antarctica) in the period from January, 20 to February, 9, 2017. Through that we can determine the total displacement vector on a point by three coordinates, they are measured by pseudo-stereopair obtained from different-time orthophotomaps and DEM. Modern automated techniques for identifying the corresponding points on a pair of images allow obtaining a sufficiently dense measurement network with predictable accuracy and precision. The investigation made it possible to determine the glacier displacement in 10 days and the distribution nature of these offsets without ground-based geodetic measurements. The average drift was 6,28 m, with a scatter from 0,07 m to 10,8 m. A method for estimating the shifts without ground control measurements was proposed and the main sources of systematic and random errors in coordinates and points heights determination were described.

THE ENHANCEMENTS IN STORAGE CAPACITY AND LONG-TERM DATA RETENTION OF MULTIDIMENSIONAL FLASH MEMORY IN MODERN MICROCIRCUIT APPLICATIONS

Generally, flash memory is a type of permanent memory for computers in which the contents can be reprocessed or erased electronically. Compared to programmable read-only memory that can erase electricity, operations on it can be performed on modules located in different locations. Flash memory is much less expensive than EEPROM, which is why it has become a dominant technology. Especially, in situations, this stable and long-term data retention is required. Its use is allowed in various cases like digital audio players, photo and video cameras, mobile phones and smartphones, and specialized Android applications on the memory card. Additionally, it is also used on USB flash drives, traditionally used to store and transfer information between computers. The proposed model provides enhancements to the storage capacity of various flash memory modules. In a saturation point, the proposed model achieved 93.03% of NOR Memory management, 89.31% of NAND Memory management, 94.25% of Ferroelectric RAM Memory management, and 94.53% of Magnetic RAM Memory management, 96.05% of Ovonic Unified Memory management and 96.16% of Salcogenide RAM Memory management.

Intraoperative Guidance Using Hyperspectral Imaging: A Review for Surgeons

Hyperspectral imaging (HSI) is a novel optical imaging modality, which has recently found diverse applications in the medical field. HSI is a hybrid imaging modality, combining a digital photographic camera with a spectrographic unit, and it allows for a contactless and non-destructive biochemical analysis of living tissue. HSI provides quantitative and qualitative information of the tissue composition at molecular level in a contrast-free manner, hence making it possible to objectively discriminate between different tissue types and between healthy and pathological tissue. Over the last two decades, HSI has been increasingly used in the medical field, and only recently it has found an application in the operating room. In the last few years, several research groups have used this imaging modality as an intraoperative guidance tool within different surgical disciplines. Despite its great potential, HSI still remains far from being routinely used in the daily surgical practice, since it is still largely unknown to most of the surgical community. The aim of this study is to provide clinical surgeons with an overview of the capabilities, current limitations, and future directions of HSI for intraoperative guidance.

Implications of free-edge effect at thin plain-woven carbon fiber reinforced plastic laminates with out-of-plane waviness under cyclic loading

The onset of damage caused by the free-edge effect in plain-woven carbon fiber reinforced plastic (CFRP) specimens with an out-of-plane waviness under tension-tension fatigue loading is investigated. Numerical calculations show that interlaminar and intralaminar stresses close to the out-of-plane waviness are higher than the equivalent stresses at the surrounding edge regions. Using submodels, the influence of the chosen out-of-plane waviness can be better assessed. The free-edge effect of the considered specimens, which originates from stress gradients between plies of different orientation, is altered by the change in the stress field caused by the out-of-plane waviness. Large interlaminar stresses between plies of the same orientation are obtained, which contrasts with existing literature. In experimental fatigue testing it is found that cracks at the free edge appeared at the predicted locations, and after reaching crack saturation, in regions close to the out-of-plane waviness, interlaminar and intralaminar stresses lead to additional cracks along the whole free edges. The experimental tests are supported by a three dimensional image correlation system (3D-DIC), a thermal-imager and a digital photographic camera, which allows detailed examination of selected areas. Visual observation during fatigue testing and post-mortem inspection show good agreement between experimental data and numerical calculations in relation to the location of the damage initiation. As a result, out-of-plane waviness at free edges must be considered as an additional significant fatigue damage initiation location in laminate analysis.

Improved Analysis of STEVE Photographs

AbstractWe present a new approach for the analysis of high‐resolution digital camera photographs taken by photographers who have fortuitous been able to capture rare events, such as the glowing sky phenomenon known as strong thermal emission velocity enhancement (STEVE). This method is especially effective with a time lapse series of images of the night sky taken under constant camera settings with a steady pointing. Stars, planets, and satellites seen in such images can be used to determine the precise and accurate registration of camera pixels to coordinates of angular altitude and azimuth. The location of satellites in the image enables precise and accurate synchronization of the images. We apply these techniques to the series of photographs of STEVE taken on July 25, 2016. We confirm the altitude structure previously found for STEVE. We find it most likely that the green picket fence features often seen during STEVE events are produced by auroral electron precipitation. With the precipitation assumption, we are able to extract novel information about the energy spectrum of the particles responsible for the production of STEVE luminosity in this particular event. Similarly, analyses of archived digital photographs may constitute a treasure trove of important data for improved understanding of rare and transient events, such as STEVE.

Development and validation of deep learning algorithms for automated eye laterality detection with anterior segment photography

This paper aimed to develop and validate a deep learning (DL) model for automated detection of the laterality of the eye on anterior segment photographs. Anterior segment photographs for training a DL model were collected with the Scheimpflug anterior segment analyzer. We applied transfer learning and fine-tuning of pre-trained deep convolutional neural networks (InceptionV3, VGG16, MobileNetV2) to develop DL models for determining the eye laterality. Testing datasets, from Scheimpflug and slit-lamp digital camera photography, were employed to test the DL model, and the results were compared with a classification performed by human experts. The performance of the DL model was evaluated by accuracy, sensitivity, specificity, operating characteristic curves, and corresponding area under the curve values. A total of 14,468 photographs were collected for the development of DL models. After training for 100 epochs, the DL models of the InceptionV3 mode achieved the area under the receiver operating characteristic curve of 0.998 (with 95% CI 0.924–0.958) for detecting eye laterality. In the external testing dataset (76 primary gaze photographs taken by a digital camera), the DL model achieves an accuracy of 96.1% (95% CI 91.7%–100%), which is better than an accuracy of 72.3% (95% CI 62.2%–82.4%), 82.8% (95% CI 78.7%–86.9%) and 86.8% (95% CI 82.5%–91.1%) achieved by human graders. Our study demonstrated that this high-performing DL model can be used for automated labeling for the laterality of eyes. Our DL model is useful for managing a large volume of the anterior segment images with a slit-lamp camera in the clinical setting.

Estimating Needle and Shoot Inclination Angle Distributions and Projection Functions in Five Larix principis-rupprechtii Plots via Leveled Digital Camera Photography

The leaf inclination angle distribution function is a key determinant that influences radiation penetration through forest canopies. In this study, the needle and shoot inclination angle distributions of five contrasting Larix principis-rupprechtii plots were obtained via the frequently used leveled digital camera photography method. We also developed a quasi-automatic method to derive the needle inclination angles based on photographs obtained using the leveled digital camera photography method and further verified using manual measurements. Then, the variations of shoot and needle inclination angle distributions due to height levels, plots, and observation years were investigated. The results showed that the developed quasi-automatic method is effective in deriving needle inclination angles. The shoot and needle inclination angle distributions at the whole-canopy scale tended to be planophile and exhibited minor variations with plots and observation years. The small variations in the needle inclination angle distributions with height level in the five plots might be caused by contrasting light conditions at different height levels. The whole-canopy and height level needle projection functions also tended to be planophile, and minor needle projection function variations with plots and observation years were observed. We attempted to derive the shoot projection functions of the five plots by using a simple and applicable method and further evaluated the performance of the new method.

Iris thickness measurements in patients with diabetic retinopathy.

The aim of the study was to investigate iris alterations in diabetic retinopathy (DR). Sixty-nine eyes of 69 patients were recruited and three groups of patients were examined: proliferative DR (n = 25), non-proliferative DR (n = 21) and healthy controls (n = 23). Macular optical coherence tomography (OCT), anterior segment iris OCT, and slit lamp digital camera photographs were taken. The thicknesses of the iris at a distance of 1 mm, 2 mm, and 3 mm from pupil margin were measured via iris OCT. Iris crypt count, furrow extent, color tone and collarette/diameter ratio were measured by means of anterior segment photography. Visual acuity, refractive error, intraocular pressure, and numbers of intravitreal injections were also recorded. The iris thickness measurements at 1 mm from pupil margin were significantly correlated with the macular thickness measurements (r = 0.32, p = 0.016). In the proliferative DR group, total number of injections were significantly correlated with the iris thickness measurements at 1 mm (r = 0.25, p = 0.04). The iris thickness measurements at distances 1 mm, 2 mm, and 3 mm from the pupil margin were similar in all of the groups (p > 0.05). Iris thickness did not correlate with age, intra-ocular pressure and collarette iris ratio in all the participants (p > 0.05). Iris thickness is similar in diabetic patients and healthy controls. Meanwhile, iris thickness near the pupillary margin is positively correlated with macular thickness.

Stop-Motion Photography Techniques

Stop-motion is an animation technique in which an object is physically manipulated and photographed on a single frame of motion picture film so that it appears to move on its own. The object is moved in small increments between individually photographed frames, creating the illusion of movement when the series of frames is played as a fast sequence. With the advent of digital imaging technology, stop-motion can also be implemented using digital photographic cameras, and not only using traditional cinematographic cameras that allow photographing a frame by frame, which contributed a lot to the spread of this technique, and also facilitated the ability to control the final results of the speed of movement With computer software specialized in combining a set of stills into one video. There are difficulties facing maintaining the continuity of the event carried out with stop-motion because there is absolutely no event at all, as well as the difficulty of maintaining homogeneity between successive frames in terms of exposure, clarity, color and composition, in addition to the difficulty of showing the reality of movement and controlling its rhythm to an already static body. Therefore, in this research we will study all the techniques of stop-motion photography, whether those related to shooting, animating or transition between different shots, in order to find out how to achieve continuity, homogeneity and realism, in films implemented with stop-motion technique.

Evaluation of Selfies and Filtered Selfies and Effects on First Impressions

Selfies and filtered selfies are becoming more prevalent throughout society and in the facial plastic surgery clinic. The term "Snapchat dysmorphia" has been used to describe patients seeking procedures to look like their selfie or filtered selfie. This is particularly frequent in the Millennial population, aged 22 to 37 years. The authors sought to determine the effects on first impression from different photograph types: selfies, filtered selfies, a rear-facing smartphone camera, and a digital camera (DC). We hypothesize that the DC photographs will have the highest rated first impressions among evaluators despite the popularity of selfies and filtered selfies. This study included 240 evaluators and 4 patients each completing the 4 different photograph types. The evaluators completed a survey rating first impression on various measures of success for each photograph type. A total of 960 first impressions were recorded for each of the 8 subscales, yielding 7680 individual assessments of first impression. The DC photograph was found to have the highest first impression scores among the 4 photograph types. There was no statistical difference between selfies and filtered selfies. The rear-facing smartphone camera received the lowest first impression scores. Our findings indicate that the standard DC photograph taken during a preoperative consultation has higher first impressions than selfies or filtered selfies. Although "Snapchat dysmorphia" may continue to be a growing trend in the near future, our findings provide important information to discuss with patients in the preoperative visit to set realistic expectations.

A Comparative Review of Methods of Using Soil Colors and their Patterns for Wetland Ecology and Management

ABSTRACTSoil color patterns are essential to understand hydrologic regime and biogeochemical processes in wetland ecosystems. Munsell Soil Color Chart (MSCC) has been traditionally and predominantly used to identify and quantify hydric soil field indicators, but several simple, low-cost alternatives have become recently available to compare their efficacy in complementing the MSCC in soil color assessment. We conducted an intensive literature review on studies utilizing different methods to identify and quantify hydric soil colors and associated patterns; these include 1) the MSCC, 2) the Nix Color Sensor, 3) mobile phone camera (MPC) and medium-end digital camera photography, and 4) colorimetry and spectrometry. A review of these methods elucidates their respective strengths and weaknesses and highlights the importance of considering study-specific attributes in determining which method to choose for field studies of hydric soil colors. Redoximorphic features (RMFs) require methods capable of capturing small and heterogeneous soil surfaces and features such that the MSCC and digital photography are the most appropriate methods; on the other hand, the Nix Color Sensor provides rapid assessment of soil color that does not necessitate rigorous training to overcome biases that might come about in more subjective methods such as the MSCC. Overall, all alternative methods reviewed have their own merits and capacity to complement measurements made by the MSCC.

Image analysis of Spirodela polyrhiza for the semiquantitative detection of copper

Digital image analysis is a processing technique that allows users to extract quantifiable data from digital images. In this study, digital camera photography was used in the determination of leaf chlorophyll content. By analyzing the degree of color change, image analysis served as a method for fast, inexpensive and non-destructive measurement of overall plant health. This study applied image analysis methods on Spirodela polyrhiza plantlets which were exposed to copper, to determine if the rate and degree of leaf color change is proportional to the concentration of copper present in the growth medium. Within 1 day, chlorophyll concentrations of plantlets grown in 2.5 mg/L and 5mg/L Cu(II)SO4 were 0.52 and 0.47 mg/g compared to a control of 0.64 mg/g. Additionally, higher copper concentrations in the growing medium resulted in higher measured mean colour distance, ΔE*ab. Plantlets grown in 2.5 mg/L and 5 mg/L Cu(II)SO4 solutions showed a ΔE*ab divergence of 0.2 and 0.25 from the control. It was concluded that the leaf color change can be used as a measure of copper concentration within the range of 1.25 mg/L and 5 mg/L” Lower concentrations of copper did not produce a consistent measurable effect on the plantlets, while higher concentrations exceeded the uptake ability of the plant and could not be accurately distinguished from one another.

Burn image segmentation based on Mask Regions with Convolutional Neural Network deep learning framework: more accurate and more convenient

BackgroundBurns are life-threatening with high morbidity and mortality. Reliable diagnosis supported by accurate burn area and depth assessment is critical to the success of the treatment decision and, in some cases, can save the patient’s life. Current techniques such as straight-ruler method, aseptic film trimming method, and digital camera photography method are not repeatable and comparable, which lead to a great difference in the judgment of burn wounds and impede the establishment of the same evaluation criteria. Hence, in order to semi-automate the burn diagnosis process, reduce the impact of human error, and improve the accuracy of burn diagnosis, we include the deep learning technology into the diagnosis of burns.MethodThis article proposes a novel method employing a state-of-the-art deep learning technique to segment the burn wounds in the images. We designed this deep learning segmentation framework based on the Mask Regions with Convolutional Neural Network (Mask R-CNN). For training our framework, we labeled 1150 pictures with the format of the Common Objects in Context (COCO) data set and trained our model on 1000 pictures. In the evaluation, we compared the different backbone networks in our framework. These backbone networks are Residual Network-101 with Atrous Convolution in Feature Pyramid Network (R101FA), Residual Network-101 with Atrous Convolution (R101A), and InceptionV2-Residual Network with Atrous Convolution (IV2RA). Finally, we used the Dice coefficient (DC) value to assess the model accuracy.ResultThe R101FA backbone network gains the highest accuracy 84.51% in 150 pictures. Moreover, we chose different burn depth pictures to evaluate these three backbone networks. The R101FA backbone network gains the best segmentation effect in superficial, superficial thickness, and deep partial thickness. The R101A backbone network gains the best segmentation effect in full-thickness burn.ConclusionThis deep learning framework shows excellent segmentation in burn wound and extremely robust in different burn wound depths. Moreover, this framework just needs a suitable burn wound image when analyzing the burn wound. It is more convenient and more suitable when using in clinics compared with the traditional methods. And it also contributes more to the calculation of total body surface area (TBSA) burned.

Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera

The permanent monitoring of vegetation cover is important to guarantee a sustainable management of agricultural activities, with a relevant role in the reduction of water erosion. This monitoring can be carried out through different indicators such as vegetation cover indices. In this study, the vegetation cover index was obtained using uncalibrated RGB images generated from a digital photographic camera on an unmanned aerial vehicle (UAV). In addition, a comparative study with 11 vegetation indices was carried out. The vegetation indices CIVE and EXG presented a better performance and the index WI presented the worst performance in the vegetation classification during the cycles of jack bean and millet, according to the overall accuracy and Kappa coefficient. Vegetation indices were effective tools in obtaining soil cover index when compared to the standard Stocking method, except for the index WI. Architecture and cycle of millet and jack bean influenced the behavior of the studied vegetation indices. Vegetation indices generated from RGB images obtained by UAV were more practical and efficient, allowing a more frequent monitoring and in a wider area during the crop cycle.

Is the high-speed camera-based method a plausible option for bar velocity assessment during resistance training?

This study aims to identify the measurement error associated with the mean movement velocity when using high-speed camera-based methods and video analysis during resistance training. Eleven resistance-trained men (26.0 ± 3.4 years) completed a progressive loading test in bench press exercise. Measurements from concentric mean velocity (MV), distance and time were obtained from a linear velocity transducer (T-Force) and videos recorded with high speed cameras on readily available smartphones (Samsung S6, Xiaomi A1, and iPhone X) and digital photo cameras (Casio FH20). Videos were examined using video analysis software (Kinovea). Despite the high correlations detected, the Bland-Altman analyses revealed that all high speed cameras produced substantial overestimation of barbell MV against high loads >60% 1RM (MV error = 0.06 ± 0.03 m·s−1 to 0.08 ± 0.04 m·s−1), but mainly against low loads <60% 1RM (MV error = 0.13 ± 0.06 m·s−1 to 0.20 ± 0.09 m·s−1). The maximum estimation error of the load being lifted (%1RM) was considerable both for low (8.5–12.7% 1RM) and high loads (13.9–22.6% 1RM). Among other practical limitations, the video-based system using different high-speed cameras and smartphone devices presents severe limitations when estimating mean concentric velocity, especially when recording low loads at high velocity.

Interpreting China: myth, nationalism and global culture

This paper argues that the analysis of specific forms of popular culture and of the Chinese media, are important phenomena to study if one wants to get insights into the socio-cultural circumstances that characterized China during the 1990s and 2000s. The transformations in the everyday life caused by the opening to global capital, and the development of the media and information technologies, along with the overwhelming use of TV, computer technologies, videorecorders, digital photocameras, the increasing use of the Internet, and the consequent growth in the communication of informations, capital and people, all these factors and many others, strongly contributed to a decisive and rapid social transformation which brought to a world of confusion, tensions and contradictions that both national myths and nationalism attempted to cope with.

Microencapsulation of Three-Component Thermochromic System for Reversible Color Change and Thermal Energy Storage

In this study, poly(methyl methacrylate)/thermochromic system (PMMA/TS) and poly(methyl methacrylate-comethacrylic acid)/thermochromic system (P(MMA-co-MA)/TS) microcapsules were prepared by using emulsion polymerization method. The thermochromic system was consisting of crystal violet lactone (CVL) as a leuco dye, bisphenol-A (BPA) as a color developer, and 1-tetradecanol (TD) as a solvent. Microcapsules with different ratio of core/shell were synthesized to examine the effect of core/shell ratio on the properties of microcapsules. Phase transition temperatures and enthalpies, morphology, and particle size distributions of the microcapsules were analyzed using differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and particle size analyzer instruments, respectively. FT-IR spectroscopy was used to prove the presence of the thermochromic system in the microcapsules. UV-Vis absorption bands of the thermochromic system (TS) and microencapsulated thermochromic system (MTS) at both below and above the melting temperature of the solvent were obtained by using a UV-Vis spectrophotometer. The visible color change depending on temperature was monitored for each microcapsule individually by using a digital camera. Spherical morphology and unimodal particle size distribution of the microcapsules were determined by means of SEM photographs and particle size distribution curve analysis. The mean particle sizes of the produced microcapsules varied in a range of 16.0-35.2 μm. The digital camera photographs and the UV-Vis absorbance curves proved that color changed between dark blue and light blue depending upon the temperature change. Meanwhile, the produced microcapsules were proven for an excellent heat storage capacity for thermal energy storage owing to phase changing of the tetradecanol solvent used in the thermochromic system. The melting enthalpy of the microcapsules ranged from 145.5 J/g to 193.4 J/g.