Conventional Digital Camera Research Articles

Evaluating the effect of sediment color on water radiance and suspended sediment concentration using digital imagery

Satellite remote sensing has been extensively used for estimating the suspended sediment concentration (SSC) in coastal and inland waters. The application of this method to smaller waterbodies, however, encounters several limitations, such as the coarse temporal and spatial resolution of satellite images, cloud coverage intercession, and inaccessibility during emergency periods. Conventional digital cameras are used for monitoring the water quality parameters in inland waters, but their application for remote sensing of SSC in inland waters is still under development. The empirical models developed to estimate SSC from digital imagery are usually site-specific and do not consider the effect of the sediment properties such as grain size and shape, sediment color, and types of minerals. The performance of digital cameras for estimating SSC is assessed in this study, and the effect of sediment color on the accuracy of this method is investigated. A series of laboratory experiments were conducted using four different colors of sediment: light gray, dark gray, light brown, and dark brown. The results showed that the red waveband reflectance of digital imagery was more sensitive to the variation of SSC than that of blue and green waveband. The sediment color evidently affected the correlation between the measured SSC and waveband reflectance, even with the same particle size distribution. Sediment with darker color showed the lowest reflectance values, whereas lighter-color sediment has the highest reflectance values. The performance of the developed SSC-reflectance regression models for all sediment colors was assessed at two river sites, i.e., Village Creek, and the West Fork Trinity River. The correlation between measured and predicted SSC for Village Creek, that had the same sediment size and color as the light gray soil, was high (R2=0.98). The correlation was relatively low (R2=0.55) for the West Fork Trinity River and dark gray soil water samples which had a similar color and different sediment sizes. The difference in sediment sizes could explain why the SSC-reflectance model derived from the dark gray soil exhibited poor performance in predicting the SSC for this site. This study demonstrated that consideration of sediment color effect in developing a remote sensing algorithm from digital imagery would result in more accurate estimations of SSC in riverine environments.

Digital Image Correlation for Cement-based Materials and Structural Concrete Testing

This paper presents the application of a low-cost digital image correlation (DIC) system for automated crack mapping. The system employed makes use of a conventional digital camera, a remote image recording controller, and an open-source digital image correlation MATLAB software Ncorr. To showcase the potential of the proposed system, two case studies involving general structural and material testing were undertaken. In the first series, the DIC system was used to study the fracture processes in a reinforced concrete beam and to investigate the influence of key input parameters on the spatial quality of strain maps obtained from the DIC analysis. In the second series, the application of the DIC method was expanded to assist in the study of complex multiple micro-crack formations in ductile cement composite testing. It is shown that the strain maps obtained from the DIC technique have a close resemblance to the actual crack patterns

Determination of stoichiometry and stability constants of iron complexes of phenanthroline, Tris(2-pyridyl)-s-triazine, and salicylate using a digital camera

The determination of stoichiometric ratios and stability constants of metal–ligand complexes is of great importance for physical, chemical, biochemical, and environmental studies and often require relatively expensive and sophisticated instruments. Herein, we introduce a simple, accurate, and low-cost method for determining these parameters by a conventional digital camera. The stoichiometric ratios and stability constants of iron complexes of 1,10-phenanthroline, 2,4,6-Tris(2-pyridyl)-s-triazine, and salicylate were determined, as model examples, using the molar ratio and the continuous variation methods. Digital images of solutions with various metal–ligand ratios were captured and analyzed, and the Yxy color absorbance and the ΔELUV color difference parameters were used as convenient analytical signals that favorably compete with conventional spectrophotometric signals. For the three studied iron complexes, the results of stoichiometric ratios and stability constants obtained from digital images were in excellent agreement with the spectrophotometric and the previously reported literature’s data.

UAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Cameras

Unmanned Aerial Vehicles (UAVs) offer excellent survey capabilities at low cost to provide farmers with information about the type and distribution of weeds in their fields. In this study, the problem of detecting the infestation of a typical weed (charlock mustard) in an alfalfa crop has been addressed using conventional digital cameras installed on a lightweight UAV to compare RGB-based indices with the widely used Normalized Difference Vegetation Index (NDVI) index. The simple (R−B)/(R+B) and (R−B)/(R+B+G) vegetation indices allowed one to easily discern the yellow weed from the green crop. Moreover, they avoided the potential confusion of weeds with soil observed for the NDVI index. The small overestimation detected in the weed identification when the RGB indices were used could be easily reduced by using them in conjunction with NDVI. The proposed methodology may be used in the generation of weed cover maps for alfalfa, which may then be translated into site-specific herbicide treatment maps.

Invisible Color Variations of Facial Erythema: A Novel Early Marker for Diabetic Complications?

Aim (1) To quantify the invisible variations of facial erythema that occur as the blood flows in and out of the face of diabetic patients, during the blood pulse wave using an innovative image processing method, on videos recorded with a conventional digital camera and (2) to determine whether this “unveiled” facial red coloration and its periodic variations present specific characteristics in diabetic patients different from those in control subjects. Methods We video recorded the faces of 20 diabetic patients with peripheral neuropathy, retinopathy, and/or nephropathy and 10 nondiabetic control subjects, using a Canon EOS camera, for 240 s. Only one participant presented visible facial erythema. We applied novel image processing methods to make the facial redness and its variations visible and automatically detected and extracted the redness intensity of eight facial patches, from each frame. We compared average and standard deviations of redness in the two groups using t-tests. Results Facial redness varies, imperceptibly and periodically, between redder and paler, following the heart pulsation. This variation is consistently and significantly larger in diabetic patients compared to controls (p value < 0.001). Conclusions Our study and its results (i.e., larger variations of facial redness with the heartbeats in diabetic patients) are unprecedented. One limitation is the sample size. Confirmation in a larger study would ground the development of a noninvasive cost-effective automatic tool for early detection of diabetic complications, based on measuring invisible redness variations, by image processing of facial videos captured at home with the patient's smartphone.

Temporal super-resolution microscopy using a hue-encoded shutter.

Limited time-resolution in microscopy is an obstacle to many biological studies. Despite recent advances in hardware, digital cameras have limited operation modes that constrain frame-rate, integration time, and color sensing patterns. In this paper, we propose an approach to extend the temporal resolution of a conventional digital color camera by leveraging a multi-color illumination source. Our method allows for the imaging of single-hue objects at an increased frame-rate by trading spectral for temporal information (while retaining the ability to measure base hue). It also allows rapid switching to standard RGB acquisition. We evaluated the feasibility and performance of our method via experiments with mobile resolution targets. We observed a time-resolution increase by a factor 2.8 with a three-fold increase in temporal sampling rate. We further illustrate the use of our method to image the beating heart of a zebrafish larva, allowing the display of color or fast grayscale images. Our method is particularly well-suited to extend the capabilities of imaging systems where the flexibility of rapidly switching between high frame rate and color imaging are necessary.

Smartphone-based chemiluminometric hybridization assays and quantitative competitive polymerase chain reaction

The present report introduces the smartphone as a simple, low-cost detector/imager for chemiluminometric hybridization assays and quantitative competitive polymerase chain reaction (QCPCR). In QCPCR the amplification products from the target and the competitor DNA have identical sizes but differ in a short sequence flanked by the primers. The products are hybridized with their cognate oligonucleotide probes, captured on microtiter wells and detected via an enzyme-catalyzed chemiluminogenic reaction using the smartphone as a detector/imager. We provide, for the first time, data on: (a) the detectability, analytical range and reproducibility of smartphone-based chemiluminometric hybridization assays of double stranded amplification products, (b) the comparison of smartphone-based detection with a conventional digital camera and a luminometer, and (c) the detectability, analytical range and reproducibility of smartphone-based QCPCR in terms of the number of copies of input target sequences in the sample prior to amplification. The limits of detection of the DNA hybridization assay based on the smartphone, digital camera and luminometer were 1.6, 2.4 and 1 pmol L−1. Smartphone-based QCPCR showed an analytical range from 137 to 9 × 105 copies of target DNA.

A hybrid SURF-DIC algorithm to estimate local displacements in structures using low-cost conventional cameras

A fast, efficient and low-cost method for the accurate determination of local displacements in structures based on computer vision techniques is presented in this study. First, displacements at pixel level are estimated using the SURF (Speeded-Up Robust Features) image matching algorithm, which detects corresponding points in the images. Then, the initial displacement estimations are refined at subpixel scale through image cross-correlation in the frequency domain. The image acquisition is simple and fast, using a conventional low-cost digital camera. The method was validated comparing the results obtained with those provided by a high performance system (ARAMIS 5 M) that integrates two cameras and image processing software. Results show that the proposed method is able to detect displacements with a precision of approximately 60% of the pixel size. The algorithm was implemented in a computer program in order to automatize the procedure.

The Use of Gigapixel Photogrammetry for the Understanding of Landslide Processes in Alpine Terrain

The work in this paper illustrates an experimental application for geosciences by coupling new and low cost photogrammetric techniques: Gigapixel and Structure-from-Motion (SfM). Gigapixel photography is a digital image composed of billions of pixels (≥1000 megapixels) obtained from a conventional Digital single-lens reflex camera (DSLR), whereas the SfM technique obtains three-dimensional (3D) information from two-dimensional (2D) image sequences. The field test was carried out at the Ingelsberg slope (Bad Hofgastein, Austria), which hosts one of the most dangerous landslides in the Salzburg Land. The stereographic analysis carried out on the preliminary 3D model, integrated with Ground Based Synthetic Aperture Radar Interferometry (GBInSAR) data, allowed us to obtain the main fractures and discontinuities of the unstable rock mass.

Artificial Intelligence to Design a Mask Insensible to the Distance From the Camera to the Scene Objects

The sharpness of an image depends on the spatial frequency response of the photographic imaging system and the sensor characteristics. In conventional digital cameras, only those objects within a distance range are in focus, while other objects are captured with different amounts of blurring depending on their distance to the focal plane. This can be desired for some applications; however, this can also be undesired because some objects in the scene may be blurred and impossible to recover. In the field of augmented reality, simulating this natural effect of showing sharp objects in combination with blurred objects increases the visual realism of augmented video. In order to simulate this effect, it is very important to capture all objects in the scene with high quality so that it could be possible to dynamically blur different objects in the scene at runtime. In this paper, we present an algorithm to find a set of possible complex-amplitude transmittance masks capable of considerably reducing the impact of focus errors in the scene objects. Computer simulations are used to compare the masks found in this paper with a classic mask in the state of the art. The main contribution of this paper is the use of Chebyshev polynomials to model an optical mask, and then, use artificial intelligence to establish some properties of this mask, such as the depth of field, the resolution, and the amount of gathered light.

Estudo comparativo entre imagens de câmera fotográfica convencional e smartphone para o telediagnóstico de tumores palpebrais.

to compare the accuracy of eyelid tumor diagnosis obtained by evaluating conventional camera images with the ones obtained by evaluating smartphone images. from January 2016 to July 2017, 36 patients underwent face-to-face external assessments and biomicroscopic examinations to establish clinical diagnoses. The lesions were photographed using Canon PowerShot SX530 HS Digital Camera (16.8 Megapixels) and Samsung GALAXY S4 smartphone camera. All lesions were resected and submitted to anatomopathological examinations. Preoperative images were sent to two specialists in eyelid diseases and then remotely analyzed. Data from in-person diagnoses and telediagnoses were compared with the gold standard of histological diagnosis. the most frequent lesions were basal cell carcinoma (33.3%), actinic keratosis (19.4%), and nevus (13.9%). Kappa coefficient for the diagnosis of malignant lesion showed agreement between the two tele-evaluators in the conventional digital camera images (0.68) and in the smartphone images (0.78). The face-to-face examiner's accuracy was of 94.4%; the tele-evaluators' accuracy in the conventional digital camera images was of 83.3% and in the smartphone images varied from 80.6% to 86.1%. Comparing the in-person diagnoses with the telediagnoses (obtained by evaluating conventional digital camera images or smartphone images), there was no significant difference in the hit rates. for eyelid tumor telediagnosis, images obtained using smartphone camera were equivalent to those obtained using conventional digital camera.

Hough Transform Implementation For Event-Based Systems: Concepts and Challenges.

Hough transform (HT) is one of the most well-known techniques in computer vision that has been the basis of many practical image processing algorithms. HT however is designed to work for frame-based systems such as conventional digital cameras. Recently, event-based systems such as Dynamic Vision Sensor (DVS) cameras, has become popular among researchers. Event-based cameras have a significantly high temporal resolution (1 μs), but each pixel can only detect change and not color. As such, the conventional image processing algorithms cannot be readily applied to event-based output streams. Therefore, it is necessary to adapt the conventional image processing algorithms for event-based cameras. This paper provides a systematic explanation, starting from extending conventional HT to 3D HT, adaptation to event-based systems, and the implementation of the 3D HT using Spiking Neural Networks (SNNs). Using SNN enables the proposed solution to be easily realized on hardware using FPGA, without requiring CPU or additional memory. In addition, we also discuss techniques for optimal SNN-based implementation using efficient number of neurons for the required accuracy and resolution along each dimension, without increasing the overall computational complexity. We hope that this will help to reduce the gap between event-based and frame-based systems.

REVERSE ENGINEERING USING PHOTOGRAMMETRY AND SEGMENTATION FOR INDUSTRIAL STRUCTURES

This paper presents an interdisciplinary approach to achieve a new working method for the three-dimensional modeling of buildings and structures. Using conventional digital cameras, the main achievement is the reduction of costs and time involved in the process of gathering information, keeping the dimensional accuracy. The results of this methodology are precise 3D models that are valid for reverse drawing documentation, structural assessment and retrofitting of existing buildings. Keywords: photogrammetry, tridimensional reconstruction, 3d modeling, structures, segmentation

Construction and comparison of 3D multi-source multi-band models for cultural heritage applications

Abstract 3D multi-band/multi-spectral reconstruction is a technique, which allows the use of images taken in different spectral bands for the reconstruction of spectrally-resolved 3D models of paintings. In this work, we propose a procedure for constructing and comparing 3D multi-band models obtained starting from a variety of input data (RGB and IR images, UV-induced fluorescence images, etc.) and/or acquired with different instruments. The procedure has been tested on two case studies, with the aim to highlight the critical issues associated to the specificities of the subject and of the environmental constrains: a 14th century panel painting signed by Barnaba from Modena, preserved at the Museum of San Matteo in Pisa, Italy and a 15th century panel painting preserved at the Regional Gallery of Palazzo Bellomo in Syracuse, Italy. RGB, IR and UV–VIS fluorescence models obtained with a conventional digital camera (RGB and UV) and a multisband camera (IR) were realized and compared, for revealing differences at sub-millimeter level.

Transdermal Optical Imaging Reveal Basal Stress via Heart Rate Variability Analysis: A Novel Methodology Comparable to Electrocardiography.

The present study examined the validity of a novel physiological measurement technology called transdermal optical imaging (TOI) technology at assessing basal stress. This technology conveniently, contactlessly, and remotely measures facial blood flow changes using a conventional digital video camera. We compared data from TOI against the pulse data collected from the FDA approved BIOPAC system. One hundred thirty-six healthy adults participated in the study. We found that TOI measurements of heart rate and heart rate variability (HRV), which reflects basal stress, corresponded strongly to those obtained from BIOPAC. These findings indicate that TOI technology is a viable method to monitor heart rate and HRV not only accurately but also conveniently, contactlessly, and remotely. Further, measures of HRV obtained via TOI serves as a valid index of basal stress. Potential applications of this technology in psychological research and other fields are discussed.

The Possibility of Using Digital Images in Assessment of Plant Canopy Development and Weed Spread

AbstractNowadays, there are various methods of plant biomass assessment available for the purposes of plant growth analysis. Visual plant coverage assessment is often subjective; the other methods are destructive or require purchasing some special devices. This paper presents the assessment of the possibilities and limitations of using digital images made by conventional digital cameras for the purposes of monitoring of the plant canopy development and weed distribution during a vegetation period using the example from the field experiment established on agricultural land in Malanta at the experimental site of the Slovak University of Agriculture. The study is focused on assessment of the effect of biochar application on gas emission, hydrophysical soil properties as well as plant response and yields and it was established in the spring of 2014. Downward images of corn (Zea maysL.) were taken during four sampling campaigns in the vegetation season 2015. Images were analysed by the BreedPix software that could estimate the portion of green fraction (count of green pixels) and thus the image-derived vegetation index (IDVI). According to the image analysis of photos taken during different sampling dates, it could be concluded that biochar addition had a positive effect on the plant growth (above ground biomass) since all treatments resulted in higher IDVIs at the end of the vegetative growth in comparison to control. Further, we assume that the increasing trend in the crop canopy growth was partially limited by competitive presence of weeds at the beginning of the study. According to our experience, we can recommend the software for temporal and spatial monitoring of agricultural crops development. The usage is limited to early growth stages. Moreover, it can be also used for assessment of the weed coverage.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

Image Retrieval in Spatial and Temporal Domains With a Quadrant Detector

To retrieve an N pixel image of a scene, conventional digital cameras record the information using an N pixelated detector with one measurement, while single-pixel imaging achieves it by sampling the image in a particular basis and recording the light intensities of N temporal measurements with a single-pixel detector. Besides these two schemes, it is also possible to obtain the same spatial information with an X pixels detector and N / X measurements, where the pressure of information retrieval is distributed to both spatial and temporal domains, rather than condensed in one domain. In this paper, we investigate this possibility and present a 4-pixels imaging scheme, which retrieves an image partially in spatial domain and partially in temporal domain, by adopting a quadrant detector to a single-pixel imaging system. While yielding images with equal quality, the proof-of-principle system we built is four times faster than a standard single-pixel imaging system, demonstrating the feasibility of the proposed scheme. Our work exploits the flexibility of space-time information retrieval and can be useful for applications where comprise between spatial and temporal domains is needed.

Cartography for Civil Engineering Projects: Photogrammetry Supported by Unmanned Aerial Vehicles

Photogrammetry has been the conventional way of gathering the necessary geodetic information to design large and medium engineering projects (highways, railroads, dams, etc.). Such methodology requires expensive and highly sophisticated technical tools, such as airplanes, metric cameras, and navigation systems, and consequently, only a few companies could afford those kinds of measurement equipment. Today, advances with unmanned aerial vehicles (UAVs) are enabling an increasing number of small companies to provide photogrammetric information for engineering projects. This paper presents a way in which an orthophoto can be made with its necessary digital terrain model in a semi-automated way. The UAV used was a fixed-wing aircraft equipped with a conventional digital camera. The pixel size on the ground (GSD) was 13 cm and the flight altitude around 285 m. After the photobundle adjustment, the error in 3D space was 12 cm. Smaller errors can be achieved by lowering the flight height.

Human eye visual hyperacuity: Controlled diffraction for image resolution improvement

The Human Visual System appears to be using a low number of sensors for image capturing, and furthermore, regarding the physical dimensions of cones—photoreceptors responsible for the sharp central vision—we may realize that these sensors are of a relatively small size and area. Nonetheless, the human eye is capable of resolving fine details thanks to visual hyperacuity and presents an impressive sensitivity and dynamic range when set against conventional digital cameras of similar characteristics. This article is based on the hypothesis that the human eye may be benefiting from diffraction to improve both image resolution and acquisition process. The developed method involves the introduction of a controlled diffraction pattern at an initial stage that enables the use of a limited number of sensors for capturing the image and makes possible a subsequent post-processing to improve the final image resolution.