Consumer-grade Digital Camera Research Articles

CAMERA CALIBRATION WITH IRRATIONAL RADIAL DISTORTION MODEL WITH ANALYTICAL SOLUTIONS

Abstract. Consumer grade digital cameras are widely used in many applications including Photogrammetric mapping and 3D modelling. One common limitation found in such cameras is radial lens distortions. To produce wide angle lenses camera manufacturers reduce the amount of barrel distortion by minimizing both the central and edge distortion profiles, resulting in a mixture of pincushion and barrel distortions for a single lens. These lenses also lack symmetry, making some of the existing distortion models almost ineffective. The mostly used model for radial distortion corrections is the polynomial model which is difficult to solve analytically especially when the model possesses many quadratic terms. Suggestions were made for division models but such models are not suitable when the lens field of view exceeds 180 degrees and exhibit some instabilities when dealing with large magnitude of distortion coefficients. Moreover mathematical formulations of some models cannot handle negative distortion coefficients. Attempts to improve the division models were made with proposals for rational models which present the advantage of handling larger distortion magnitude with fewer terms. However some of these models do not account for all the distortion coefficients in their solutions, limiting the potential of the techniques. This study presents an irrational distortion model with analytical solutions. The proposed model was tested with imagery captured by wide angle lenses and the experimental results reveal that the technique produced the best estimates of radial distortion coefficients. The proposed model was also able to capture image distortions originating from projection errors by the wide angles lenses used in this study.

A SYSTEM FOR MONITORING OF UAV CAMERA ORIENTATION: DESIGN AND INITIAL ANALYSIS

Abstract. Many unmanned aerial vehicles (UAV) that are used for aerial mapping are equipped with consumer-grade digital cameras, which use CMOS (Complementary metal–oxide–semiconductor) image sensors. Majority of these sensors capture images using an electronic rolling shutter, which can cause distortions on the image if either the camera or the captured objects are moving. This phenomenon is usually ignored in aerial mapping with UAVs in practice. However, there is a lack of published research papers that would prove the effect can be neglected. In this paper, we present the design of the system for monitoring UAV camera orientation. Furthermore, the calibration process to get correct and reliable readings is described. The initial analysis of the data is focused on assessing the accuracy that can be achieved using the proposed system. The main component of our system is a MEMS (Microelectromechanical system) gyroscope. It was selected for its low weight and size, low price and high sampling rates which are all very beneficial characteristics for a system, mounted on a UAV. In a paper, a working prototype is presented that uses the selected MEMS gyroscope connected to a single-board computer. The presented initial analysis of collected data shows, that the system would be capable to indirectly detect the image distortions, caused by camera orientation changes during exposure, in the range of typical ground sample distance (GSD).

Mixed reality and remote sensing application of unmanned aerial vehicle in fire and smoke detection

Abstract This paper proposes the development of a system incorporating inertial measurement unit (IMU), a consumer-grade digital camera and a fire detection algorithm simultaneously with a nano Unmanned Aerial Vehicle (UAV) for inspection purposes. The video streams are collected through the monocular camera and navigation relied on the state-of-the-art indoor/outdoor Simultaneous Localisation and Mapping (SLAM) system. It implements the robotic operating system (ROS) and computer vision algorithm to provide a robust, accurate and unique inter-frame motion estimation. The collected onboard data are communicated to the ground station and used the SLAM system to generate a map of the environment. A robust and efficient re-localization was performed to recover from tracking failure, motion blur, and frame lost in the data received. The fire detection algorithm was deployed based on the color, movement attributes, temporal variation of fire intensity and its accumulation around a point. The cumulative time derivative matrix was utilized to analyze the frame-by-frame changes and to detect areas with high-frequency luminance flicker (random characteristic). Color, surface coarseness, boundary roughness, and skewness features were perceived as the quadrotor flew autonomously within the clutter and congested area. Mixed Reality system was adopted to visualize and test the proposed system in a physical environment, and the virtual simulation was conducted through the Unity game engine. The results showed that the UAV could successfully detect fire and flame, autonomously fly towards and hover around it, communicate with the ground station and simultaneously generate a map of the environment. There was a slight error between the real and virtual UAV calibration due to the ground truth data and the correlation complexity of tracking real and virtual camera coordinate frames.

Improving nitrogen assessment with an RGB camera across uncertain natural light from above-canopy measurements

The farming activities in developing countries are mostly conducted in daytime with varying intensities of natural light throughout the day. Also, the shade trees can further increase the uncertainty of natural light exposure on plants. This research proposes an appropriate method to standardize index values obtained from an RGB digital camera for assessing biophysical properties, especially nitrogen content. Nutrient content in plants is an important factor that characterizes plant yields and health. Determining the status of plant nutrients often requires field observation. The conventional laboratory methods and remote sensing applications (i.e. satellite, airborne and spectrometer) are still expensive. Also, weather and field condition significantly affect the quality of measurement results. The use of consumer-grade digital cameras has been explored as an alternative low-cost tool for non-scientific end users; however, the use of a camera for above-canopy measurement is severely constrained by unfavorable weather condition coupled with limited time available for the measurement that depends on the intensity of incident light and the condition of plantation area. Furthermore, shade trees present in plantation areas reduce the quality of measurement results. By using this newly proposed method, measurement accuracy is improved and the potential use of Red, Green, and Blue (RGB) cameras during daytime is explored. Since many studies showed that the Hue index was a potential tool for estimating biological properties, this study used exposure value (EV) to adjust the digital number (DN) and Hue index to observe the potential of calibrated and standardized DN and Indices for estimating greenness of Robusta coffee plants.

Comparative Analyses of the Point Cloud Produced by Using Close-Range Photogrammetry and Terrestrial Laser Scanning for Rock Surface

Point cloud produced by using theoretically and practically different techniques is one of the most preferred data types in various engineering applications and projects. The advanced methods to obtain point cloud data in terrestrial studies are close range photogrammetry (CRP) and terrestrial laser scanning (TLS). In the TLS technique, separated from the CRP in terms of system structure, denser point cloud at certain intervals can be produced. However, point clouds can be produced with the help of photographs taken at appropriate conditions depending on the hardware and software technologies. Adequate quality photographs can be obtained by consumer grade digital cameras, and photogrammetric software widely used nowadays provides the generation of point cloud support. The tendency and the desire for the TLS are higher since it constitutes a new area of research. Moreover, it is believed that TLS takes the place of CRP, reviewed as antiquated. In this study that is conducted on rock surfaces located at Istanbul Technical University Ayazaga Campus, whether point cloud produced by means photographs can be used instead of point cloud obtained by laser scanner device is investigated. Study is worked on covers approximately area of 30 m × 10 m. In order to compare the methods, 2D and 3D analyses as well as accuracy assessment were conducted. 2D analysis is areal-based whereas 3D analysis is volume-based. Analyses results showed that point clouds in both cases are similar to each other and can be used for similar other studies. Also, because the factors affecting the accuracy of the basic data and derived product for both methods are quite variable, it was concluded that it is not appropriate to make a choice regardless of the object of interest and the working conditions.

Radiometric calibration framework for ultra-high-resolution UAV-derived orthomosaics for large-scale mapping of invasive alien plants in semi-arid woodlands: Harrisia pomanensis as a case study

ABSTRACTOrthomosaics derived from consumer grade digital cameras on board unmanned aerial vehicles (UAVs) are increasingly being used for biodiversity monitoring and remote sensing of the environment. To have lasting quantitative value, remotely sensed imagery should be calibrated to physical units of reflectance. Radiometric calibration improves the quality of raw imagery for consistent quantitative analysis and comparison across different calibrated imagery. Moreover, calibrating remotely sensed imagery to units of reflectance improves its usefulness for deriving quantitative biochemical and biophysical metrics. Notwithstanding the existing radiometric calibration procedures for correcting single images, studies on radiometric calibration of UAV-derived orthomosaics remain scarce. In particular, this study presents a cost- and time-efficient radiometric calibration framework for designing calibration targets, checking scene illumination uniformity, converting orthomosaic digital numbers to units of reflectance, and accuracy assessment using in situ mean reflectance measurements (i.e. the average reflectance in a particular waveband). The empirical line method was adopted for the development of radiometric calibration prediction equations using mean reflectance values measured in only one spot within a 97 ha orthomosaic for three wavebands, i.e. red, green and blue of the Sony NEX-7 camera. A scene illumination uniformity check experiment was conducted to establish whether 10 randomly distributed regions within the orthomosaic experienced similar atmospheric and illumination conditions. This methodological framework was tested in a relatively flat terrain semi-arid woodland that is invaded by Harrisia pomanensis (the Midnight Lady). The scene illumination uniformity check results showed that at a 95% confidence interval, the prediction equations developed using mean reflectance values measured from only one spot within the scene can be used to calibrate the entire 97 ha RGB orthomosaic. Furthermore, the radiometric calibration accuracy assessment results showed a correlation coefficient r value of 0.977 (p < 0.01) between measured and estimated reflectance values with an overall root mean square error of 0.063. These findings suggest that given the entire scene being mapped is experiencing similar atmospheric and illumination conditions, then prediction equations developed using mean reflectance values measured in only one spot within the scene can be used to calibrate the entire orthomosaic in semi-arid woodlands. The proposed methodological framework can potentially be tested and adapted for use in large-scale crop mapping and monitoring in precision agriculture, land-use/land-cover classification as well as plant species delimitation, particularly for mapping widespread invasive alien plants such as H. pomanensis.

An investigation of the spectral and radiometric characteristics of low-cost digital cameras for use in UAV remote sensing

ABSTRACTThe foundation of all quantitative remote sensing is based on the ability of sensors to convert energy into digital signals. This process requires an understanding of the radiometric and spectral behaviour of the instrument. This information is rarely available for the consumer-grade digital cameras commonly used in unmanned aerial vehicle (UAV) systems. This study measured the spectral and radiometric characteristics of consumer-grade digital cameras in laboratory-based experiments. The spectral characteristics showed broad overlapping spectral bands in the visible and near-infrared wavelengths with spectral band widths between 70 and 100 nm. The radiometric response functions were non-linear in nature. The nonlinearity resulted in the inability of reliable spectral reflectance calculations. When compared to the spectral reflectance values computed from an ASD FieldSpec-3, differences were as high as 42% from the true value with average deviations between 23% and 32%. When characterized, the spectral reflectance values compared more favourably to ASD-computed spectral reflectance.

2126 Optimizing a technique for visualizing retinal and choroidal blood flow noninvasively

OBJECTIVES/SPECIFIC AIMS: Diabetic retinopathy is an increasingly prevalent disease, difficult to screen for across the globe. We have developed and began optimizing an innovative technique to visualize and quantify retinal blood flow, to elucidate the role of the choroid in retinal pathologies such as diabetic retinopathy or choroidopathy. METHODS/STUDY POPULATION: Preliminary retinal was obtained from a surgical retina video library (Truvision, Goleta, CA, USA). Videos of different organs were recorded while vessels were occluded via a blood pressure cuff, using consumer-grade digital video cameras (NEX-5T, a7sii; Sony, New York, NY, USA). All other retinal videos were taken using a fundus camera (50×; Topcon, Oxland, NJ, USA) modified to support the above digital video cameras. All videos were processed using experimental software (MATLAB, Mathworks, Natick, MA, USA). RESULTS/ANTICIPATED RESULTS: Video imaging of the retina was optimized for lighting conditions and software requirements. Parameters were defined for the software imaging pipeline, such as frequency range of interest, sampling rate, and noise minimization. Software was developed to stabilize frames, accounting for eye saccades. Use of a biosensor enabled accurate measurement of pulse waveform, increasing signal-to-noise ratio. The optimal light requirements were determined such that adequate exposure of the retina is reproducible yet still comfortable for use in human subjects. DISCUSSION/SIGNIFICANCE OF IMPACT: This novel technique allows for an inexpensive, noninvasive, and reproducible ocular blood flow imaging platform. By optimizing this technique, we can proceed with our future plans for a pilot study to compare our imaging technique with the current standard, paving the way for future clinical studies.

Image Registration-Based Bolt Loosening Detection of Steel Joints.

Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts.

Using ground observations of a digital camera in the VIS-NIR range for quantifying the phenology of Mediterranean woody species

The spectral reflectance of most plant species is quite similar, and thus the feasibility of identifying most plant species based on single date multispectral data is very low. Seasonal phenological patterns of plant species may enable to face the challenge of using remote sensing for mapping plant species at the individual level. We used a consumer-grade digital camera with near infra-red capabilities in order to extract and quantify vegetation phenological information in four East Mediterranean sites. After illumination corrections and other noise reduction steps, the phenological patterns of 1839 individuals representing 12 common species were analyzed, including evergreen trees, winter deciduous trees, semi-deciduous summer shrubs and annual herbaceous patches. Five vegetation indices were used to describe the phenology: relative green and red (green\\red chromatic coordinate), excess green (ExG), normalized difference vegetation index (NDVI) and green-red vegetation index (GRVI). We found significant differences between the phenology of the various species, and defined the main phenological groups using agglomerative hierarchical clustering. Differences between species and sites regarding the start of season (SOS), maximum of season (MOS) and end of season (EOS) were displayed in detail, using ExG values, as this index was found to have the lowest percentage of outliers. An additional visible band spectral index (relative red) was found as useful for characterizing seasonal phenology, and had the lowest correlation with the other four vegetation indices, which are more sensitive to greenness. We used a linear mixed model in order to evaluate the influences of various factors on the phenology, and found that unlike the significant effect of species and individuals on SOS, MOS and EOS, the sites' location did not have a direct significant effect on the timing of phenological events. In conclusion, the relative advantage of the proposed methodology is the exploitation of representative temporal information that is collected with accessible and simple devices, for the subsequent determination of optimal temporal acquisition of images by overhead sensors, for vegetation mapping over larger areas.

Derivation of High Spatial Resolution Albedo from UAV Digital Imagery: Application over the Greenland Ice Sheet

Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

Enhanced broadband greenness in assessing Chlorophyll a and b, Carotenoid, and Nitrogen in Robusta coffee plantations using a digital camera

Direct-leaves measurement of spectral indices using a digital camera with a portable small chamber and custom illumination is used to take images of 600 leaves from 40 coffee plants. In this research, several vegetation indices (VIs) are developed and evaluated. Through a series of experiments, Chlorophyll a and b, Carotenoids, and Nitrogen critical level of Robusta coffee plants are analyzed and evaluated using selected VIs obtained from spectra of different tools like Spectrometer, digital camera, and SPAD-502 Chlorophyll meter. The actual Nitrogen critical level was determined using Kjeldahl laboratory test. Beside Hue, the newly proposed VIs could significantly improve the correlation in estimating photosynthetic pigments (Chlorophyll a and b, Carotenoids) and Nitrogen critical level of Robusta coffee plant. Finally, consumer-grade digital camera with custom chamber is shown to be used for rapid and accurate in situ estimation of Chlorophyll a and b, Carotenoids, and Nitrogen critical level of Robusta coffee plant from direct-leaves measurement.

Evaluating NIR-Red and NIR-Red edge external filters with digital cameras for assessing vegetation indices under different illumination

Consumer-grade digital cameras with or without external filters are recognized as a cost-effective method of vegetation monitoring. These cameras could produce time series information related to biophysical properties of vegetation. This paper evaluates the use of low-cost external filters with digital cameras for assessing vegetation indices (VIs). The system was implemented for ground-based (handheld) remote sensing in assessing biophysical properties of vegetation like plant phenology and Chlorophyll content. It also has high potential for above-canopy measurement using low-altitude remote sensing (LARS). In this study the modified cameras were used to capture near-infrared (NIR), red-edge (RE), and red (R) bands using proposed external filters. We use the low-cost NIR-R and NIR-RE external filters with modified cameras and tested the cameras performance using custom chamber under different illumination. Based on our findings, a method was proposed for enhancing the value of VI, which comprised the extracted DN of two broadbands like NIR and R. New ranges of broadband in red edge area (REhigh and RElow) are proposed as alternative bands in estimating Chlorophyll content. In addition, evaluation and implementation for assessing VIs are detailed in this study.

Identification and Counting of Soybean Aphids from Digital Images Using Shape Classification

Abstract. Soybean aphids are serious pests, causing negative yield impacts in the crop. Assessing their population is essential for making appropriate pesticide application decisions. Manual identification and counting, which is commonly performed to determine the economic threshold level, is time-consuming, laborious, and causes visual fatigue. In this study, an automatic image processing method was developed to identify and count aphids as well as exoskeletons and leaf spots on soybean leaves based on shape analysis. Aphid-infested soybean trifoliates were obtained at three infestation rates (low, medium, and high). Images of the front sides of the leaves were captured in the laboratory with three cameras (digital single-lens reflex or DSLR, consumer-grade digital, and smartphone) under two lighting conditions (direct and indirect). The shape parameters considered were area, perimeter, convex area, eccentricity, aspect ratio, solidity, hollowness, and roundness. Among the shape parameters tested, hollowness was the best in identifying aphids and was therefore used for developing the object classification algorithm. Of the three cameras tested, images from the consumer-grade digital camera produced the best identification accuracy (&amp;gt;82.4%), followed by the DSLR camera (&amp;gt;81.2%) and smartphone camera (&amp;gt;37.9%). Statistical analysis revealed that the accuracies did not differ significantly under different lighting conditions (p = 0.43), but the accuracies differed for the smartphone camera compared to the DSLR and consumer-grade digital cameras (p = 8.87 × 10-10). The results of automatic and manual counting were very well correlated (r = 0.92). The automatic image processing method achieved more rapid counting (&amp;lt;2 s per image after loading the image) compared to manual counting (~5 min per image). The developed approach for aphid identification and counting can be easily applied to other pest identification issues with minor modifications to the algorithm. Keywords: Aphids, Classification, Image processing, Segmentation, Shape analysis, Soybean.

Rapid Updating and Improvement of Airborne LIDAR DEMs Through Ground-Based SfM 3-D Modeling of Volcanic Features

We present a workflow to create, scale, georeference, and integrate digital elevation models (DEMs) created using open-source structure-from-motion (SfM) multiview stereo (MVS) software into existing DEMs (as derived from the light detection and ranging data in the presented cases). The workflow also maps the root-mean-square error between the base DEM and the SfM surface model. This allows DEM creation from field-based surveys using consumer-grade digital cameras with open-source and custom-built software. We employ this workflow on three examples of different scales and morphology: 1) a scoria cone on Mt. Etna; 2) a lava channel on Mauna Ulu (Kīlauea); and 3) a flank collapse scar on Mt. Etna. This represents a new approach for rapid low-cost construction and updating of existing DEMs at high temporal and spatial resolutions and for areas of up to several thousand square meters. We assess the self-consistency of the method by comparison of DEMs of the same features, created from independent data sets acquired on the same day and from the same vantage points. We further evaluate the effect of grid cell size on the reconstruction error. This method uses existing DEMs as a georeferencing tool and can therefore be used in limited access and potentially hazardous areas as it no longer relies exclusively on control targets on the ground.

Automatic time-series quantification of bluff erosion using a single consumer grade camera as basis for erosion risk assessment and forecasts – a Boston Harbor Islands case study

Many communities along coastlines and riverbanks are threatened by water erosion and hence an accurate model to predict erosion events is needed in order to plan mitigation strategies. Such models need to rely on readily available meteorological data that may or may not be correlated with the occurrence of erosion events. Computing these correlations requires a quantified index that reports the magnitude of erosion events over time. This study introduces a method to create erosion indices using affordable consumer grade digital cameras. It is able to detect and quantify erosion using an image series obtained from just one such camera by segmenting each images instance into equally sized squares that can be preprocessed and analyzed separately. This approach isolates each image segment from noise and temporary disturbances that frequently occur throughout images taken with low cost cameras. In this fashion, noise may either be addressed locally or simply ignored if it is too extreme. After preprocessing, comparison of subsequent segments yields change matrices that form the basis for segment-specific erosion indices that are later combined into a composite value for the entire image instance. Whenever a segment instance is unavailable or unusable, the algorithm attempts to use neighboring instances whenever possible. When tested against human observation of erosion events during a 6 week period, the resulting index achieves a true positive rate of 67% while producing only a small number of false positives. Finally, the index is validated by significant correlation with various meteorological data streams.

3D accident reconstruction using low-cost imaging technique

This research is about the implementation of close range photogrammetry (CRP) technique to investigate the traffic accident scene. CRP technique representing and measuring the 3D objects using data stored in 2D photographs. It is non-contact measurement requiring multiple pictures capture to measure objects of interest. Currently, a police officer uses a conventional technique to collect data on traffic accident scene using tape measurement in order to reconstruct the accident scene. The development of camera technology increases the efficiency, stability of consumer grade digital cameras for photogrammetric applications. This development can help police officer to apply a CRP technique for data collection on traffic accident scene. CRP technique offers fast data acquisition, and only need one officer during data capture. This research is to investigate traffic accident scene using the imaging technique. The methodology of this research used a measuring tape and total station for data acquisition on traffic accident scene. This research also evaluates the accuracy of data based on mathematical model standard deviation and root mean square error (RMSE). Based on this research, the implementation of CRP in accident reconstruction is very effective because can achieve a cm-level accuracy in range 40m traffic accident scene.

Combined Static and Dynamic Platform Calibration for an Aerial Multi-Camera System

Multi-camera systems which integrate two or more low-cost digital cameras are adopted to reach higher ground coverage and improve the base-height ratio in low altitude remote sensing. To guarantee accurate multi-camera integration, the geometric relationship among cameras must be determined through platform calibration techniques. This paper proposed a combined two-step platform calibration method. In the first step, the static platform calibration was conducted based on the stable relative orientation constraint and convergent conditions among cameras in static environments. In the second step, a dynamic platform self-calibration approach was proposed based on not only tie points but also straight lines in order to correct the small change of the relative relationship among cameras during dynamic flight. Experiments based on the proposed two-step platform calibration method were carried out with terrestrial and aerial images from a multi-camera system combined with four consumer-grade digital cameras onboard an unmanned aerial vehicle. The experimental results have shown that the proposed platform calibration approach is able to compensate the varied relative relationship during flight, acquiring the mosaicing accuracy of virtual images smaller than 0.5pixel. The proposed approach can be extended for calibrating other low-cost multi-camera system without rigorously mechanical structure.

Determining factors that impact the calibration of consumer-grade digital cameras used for vegetation analysis

ABSTRACTDigital cameras can collect quantitative leaf data, such as chlorophyll content and leaf area index (LAI), because they act as a simple broadband radiometer. However, a cross-calibration between cameras is needed for the purpose of extracting vegetation information from various image repositories. The objective of this study was to examine the variation between multiple consumer-grade camera types – single reflex lens (SLR), point-and-shoot, and cellphone cameras – for the purpose of collecting reliable quantitative data when monitoring vegetation. The specific objectives were to: 1) identify the optimal light conditions for the calibration procedure, 2) determine the variability of exposure value (EV)-corrected calibrated digital numbers (cDNev) values among eight consumer-grade digital cameras, and 3) compare the cDNev values with the raw digital numbers (DN), exposure-adjusted digital numbers (DNev), and calibrated digital numbers (cDN) as these latter three components are easier to compute. This study demonstrated that light intensity was important for calibrating cameras to ensure sensor saturation, and that an improper white-balance setting can negatively impact data collection. In one experiment, the coefficient of variation (CV) between the eight cameras examined in the study was reduced from 29% using raw DN to 16% using cDNev values. Likewise, the root mean square error in estimating leaf chlorophyll-a using a common vegetation index for digital camera, excess green index (EGI), was reduced from 131 to 96 mg g−2. However, for both experiments, there was only a weak statistical difference between cDNev and DNev, indicating that exposure information was the most useful in minimizing the differences between cameras. Although digital cameras are not nearly as accurate as specialized remote-sensing equipment, they do offer the potential for greater collection opportunities. This study demonstrates the potential of using consumer-grade digital cameras to derive quantitative information from citizen science projects.

Testing the accuracy of timing reports in visual timing tasks with a consumer-grade digital camera.

This study tested the accuracy of a visual timing task using a readily available and relatively inexpensive consumer grade digital camera. A visual inspection time task was recorded using short high-speed video clips and the timing as reported by the task's program was compared to the timing as recorded in the video clips. Discrepancies in these two timing reports were investigated further and based on display refresh rate, a decision was made whether the discrepancy was large enough to affect the results as reported by the task. In this particular study, the errors in timing were not large enough to impact the results of the study. The procedure presented in this article offers an alternative method for performing a timing test, which uses readily available hardware and can be used to test the timing in any software program on any operating system and display.