Non-metric Camera Research Articles

ACCURACY ASSESSMENT OF 3D PHOTOGRAMMETRIC MODEL FROM UNMANNED AERIAL VEHICLE SYSTEM

Unmanned aerial vehicle (UAV) or well known as a drone is a common technique that has been used in the geospatial field for various applications as well as in three-dimensional modelling application. The UAV is an aerial vehicle that does not carry a human pilot, fly remotely or autonomous and able to carry a sensor to collect data. Nowadays, UAV has been widely used in three-dimensional modelling application around the world. It can model an accurate object in a three-dimensional view; besides that, it also can offer a cheaper solution than other techniques or systems. Therefore, the objectives of this research are to evaluate the accuracy assessment of the 3D building model that is generated from a non-metric camera integrated with a multi-rotor UAV system and also to investigate the effect of camera angle toward the quality of the 3D building model. Block T06 of the Faculty of Built Environment and Surveying was selected as a study area in this study. This building is under the management of Universiti Teknologi Malaysia, located in the district of Skudai, Johor. The quadcopter UAV system has been used to capture the high resolution of the building's aerial image from two different perspectives: nadir and oblique. Each set of aerial images were processed using photogrammetric software for producing a three-dimensional model of Blok T06. Two types of 3D building model have produced in this study which are 3D model-based nadir and oblique aerial photo and 3D model based on nadir aerial photo. Ground control point (GCP) and check point (CPs were established in the study area using the GPS rapid-static technique. Later, the processing of aerial triangulation and accuracy assessment were implementing using these points. A statistical equation was used for evaluating the quality of the three-dimensional model was generated in this research. 3D building model based on nadir and oblique aerial photo is more accurate with RMSE ±1.008m compared 3D building model-based nadir aerial photo with RMSE ±1.145m. In conclusion, the 3D building model of block T06 was successfully produced from UAV data based on UAV photogrammetry and the angle of camera also contributes towards the quality of 3D model in aerial photogrammetry.

Method of Improving Incomplete Spatial-Temporal Data in Inland Navigation, on the Basis of Industrial Camera Images – West Oder River Case Study

Abstract Main aim of the paper is to use a single non-metric camera to support the determination of the position of. Authors propose to use the existing infrastructure of CCTV cameras mounted on bridges and wharves to determine the position of inland waterway vessels. Image from cameras giving the pixel coordinates of moving object is transformed to the geodetic data domain using a modified projective transformation method. Novel approach is to use of Sequential Projection Transformation (SPT) which additionally uses virtual reference points. The transformation coefficients calculated using the virtual points are used to determine the position of the vessels and are also simultaneously used to calibrate the industrial camera. The method has been verified under real conditions, and the results obtained are average 30% more accurate compared to the traditionally used projective transformation using a small number of real points.

Focal Length Lens Effect at Non-Metric Camera for Three-Dimensional Models Result

Selections of non-metric cameras can be calculated properly starting from choosing the right camera sensor size and lens focal length to get better results. Differences in the choice of focal length in shooting can affect the resulting photo. The resulting photo may differ from how much of the object is captured and may suffer distortion due to different selections of the focal length. The purpose of this study is to show the magnitude of the effect of focal length variation in making a three-dimensional model based on the comparison of the results of the three-dimensional model visualization, the comparison of the results of geometric accuracy based on the independent checkpoint coordinate data, and the comparison of the distance results between retro targets. The results of this study indicate that a focal length of 70 mm has better results with the formation of the object completely resembling its original object compared to a focal length of 28 mm which is not good at forming a safety pillar on the bridge. The results of the RMSE value based on ICP coordinate data at a focal length of 70 mm are better with a value of 0.083 m compared to a focal length of 28 mm with a large value of 0.123 m. The results of the RMSE value based on the distance between retro targets at a focal length of 70 mm are better with a value of 0.003 m compared to a focal length of 28 mm with a large value of 0.004 m.

Multitemporal UAV Photogrammetry For Sandbank Morphological Change Analysis: Evaluations of Camera Calibration Methods, Co-Registration Strategies, and the Reconstructed DSMs

Sandbank morphology is a longshore corridor with fast morphological changes. To analyze its changes, unmanned aerial vehicle (UAV) is the preferred effective and flexible data collection platform, which can collect very high resolution (VHR) images. UAV campaigns along corridor areas require well-distributed ground control points (GCP) and accurate geotagged image positions to avoid misalignment errors of generated digital surface models (DSMs). However, a sandy terrain can make the measurement of GCPs difficult or even impossible. Furthermore, UAVs are often equipped with consumer-grade devices (onboard GNSS and non-metric cameras), which, therefore, cannot provide accurate image positions and lead to geometric distortions of the image network due to inappropriate lens distortion corrections. This paper proposes a strategy to calibrate the used camera and co-register multi-temporal images without the need for accurate geotagged information on the whole datasets and well-distributed GCPs. The proposed strategy includes two improvements. First, we performed semi-on-the-job self-calibration (semi-OTJSC) using UAV images with favor orientations and flight altitudes to pre-calibrate interior orientation parameters (IOPs) and additional lens distortion parameters. This was then followed by another OTJSC of IOPs involving images with accurate geotagged positions. Second, a “transferred aerial-triangulation (Trans-AT)” strategy is proposed to co-register two consecutive UAV datasets through AT procedure similar to GNSS-supported AT within a strip image block (SIB). The experimental results revealed that the proposed method provides the best-fit camera parameters and generates high-accuracy co-registered DSMs. This strategy contributes significantly to multi-temporal camera calibration and co-registration procedures for determining morphological changes in corridor mapping.

Исследование точности формирования снимка камерами со шторно-щелевым затвором при съемке с беспилотных воздушных судов

Quite often aerial survey made by unmanned aerial vehicle (UAV) is carried out using digital non-metric cameras that have rolling shutters. Variations in speed of a UAV and its angular elements of exterior orientation during aerial survey cause distortions in the images generated by the camera, which affects the accuracy of the processing results. The article shows the variations in the elements of exterior orientation during the operation of a rolling shutter and describes the way of its detection by flight recorder. The values of image distortion, caused by the variations in the angular elements of the exterior orientation of a snapshot, are calculated for the Sony Alpha A6000 digital non-metric camera.

Documenting historical monuments using smartphones: a case study of Fakih Dede Tomb, Konya

Cultural heritage and historical monuments are the memories of societies and enable future generations to learn about the past. However, historical monuments from the past to the present have been subjected to many destructions, natural or unnatural. Thanks to advances in technology, it is easier to document historical monuments using digital photogrammetric methods. Today, we see the methods used in documenting historical artifacts as traditional measurement, laser scanning, and photogrammetric methods or combinations of them. In this study, historical artifacts were tried to be documented through close-up photogrammetry methods, which is a sub-working area of photogrammetry, through images taken with non-metric cameras of smartphones that we use frequently in our daily lives. Planned geodesic measurement and photography should be done in order to perform three-dimensional (3D) modeling with close-up photogrammetry. During the study, the checkpoints were measured using geodesic methods on the historical monument and part of it was reserved for accuracy analysis. The tomb of Fakih Dede in Konya, which is an important point of visit in the region has been chosen.

CALIBRATION OF NON-METRIC UAV CAMERA USING DIFFERENT TEST FIELDS

The paper deals with the calibration of a non-metric digital camera Nikon EOS 6D with a 50 mm lens that could be adapted as a potential UAV sensor for the purposes of aerial inspections. The determination of the internal orientation parameters and the image errors of the non-metric digital camera involved self-calibration with Agisoft Metashape software solving the network of the images obtained from different test fields: a chessboard field, a professional laboratory field and a spatially diverse research area. The results of the control measurement for the examined object distance of 6 meters do not differ significantly. The RMSE from the control measurement for the second analyzed object distance of 15 meters was calculated on the basis of the internal orientation elements. The images from the laboratory field, the spatial test area and the chessboard field were used, and the obtained results amounted to 7.9, 9.9 and 11.5 mm, respectively. The conducted studies showed that in the case of very precise photogrammetric measurements performed by means of the Nikon EOS 6D camera equipped with a 50 mm lens, it is optimal to conduct calibration in a laboratory test field. The greatest RMSE errors were recorded for the control images with the elements of the internal camera orientation calculated on the basis of the chessboard area. The results of the experiments clearly show a relation between the accuracy of the Nikon EOS 6D camera calibrations and the percentage of the frame area filled with the test field. This explains why the weakest calibration results were obtained from the chessboard test field.

ACHIEVING CLOSE RANGE PHOTOGRAMMETRY WITH NON-METRIC MOBILE PHONE CAMERAS

Close range photogrammetry (CRP) has gained increasing relevance over the years with its principles and theories being applied in diverse applications. Further supporting this trend, the current increase in the wide spread usage of mobile phones with high resolution cameras is expected to further popularize positioning by CRP. This paper presents the results of an experimental study wherein two (2) non-metric mobile phone cameras have been used to determine the 3-D coordinates of points on a building by using the collinearity condition equation in an iterative least square bundle adjustment process in MATLAB software environment. The two (2) mobile phones used were Tecno W3 and Infinix X509 phones with focal lengths of 5.432 mm and 8.391 mm respectively. Statistical tests on the results obtained shows that there is no significant difference between the 3-D coordinates obtained by ground survey and those obtained from both cameras at 99% confidence level. Furthermore, the study confirmed the capability of non-metric mobile phone cameras to determine 3D point positions to centimeter level accuracy (with maximum residuals of 11.8 cm, 31.0 cm, and 5.9 cm for the Tecno W3 camera and 14.6 cm, 16.1 cm and 1.8 cm for the Infinix X509 camera in the Eastings, Northings and Heights respectively).

UAV Photogrammetry under Poor Lighting Conditions-Accuracy Considerations.

The use of low-level photogrammetry is very broad, and studies in this field are conducted in many aspects. Most research and applications are based on image data acquired during the day, which seems natural and obvious. However, the authors of this paper draw attention to the potential and possible use of UAV photogrammetry during the darker time of the day. The potential of night-time images has not been yet widely recognized, since correct scenery lighting or lack of scenery light sources is an obvious issue. The authors have developed typical day- and night-time photogrammetric models. They have also presented an extensive analysis of the geometry, indicated which process element had the greatest impact on degrading night-time photogrammetric product, as well as which measurable factor directly correlated with image accuracy. The reduction in geometry during night-time tests was greatly impacted by the non-uniform distribution of GCPs within the study area. The calibration of non-metric cameras is sensitive to poor lighting conditions, which leads to the generation of a higher determination error for each intrinsic orientation and distortion parameter. As evidenced, uniformly illuminated photos can be used to construct a model with lower reprojection error, and each tie point exhibits greater precision. Furthermore, they have evaluated whether commercial photogrammetric software enabled reaching acceptable image quality and whether the digital camera type impacted interpretative quality. The research paper is concluded with an extended discussion, conclusions, and recommendation on night-time studies.

IMPLEMENTATION OF CLOSE RANGE PHOTOGRAMMETRY USING MODERN NON-METRIC DIGITAL CAMERAS FOR ARCHITECTURAL DOCUMENTATION

The development of applied geodetic techniques for mapping and documentation of historical structures, buildings and sites is an important and vital purpose for contribution of any recording of cultural heritage for any country such as Egypt. This is done to preserve and restore any valuable architectural or other cultural monument, as a support to architectural, archaeological and other art-historical research throughout the ages. The purpose of this paper is to use close range photogrammetry technique (CRP) to reconstruct 3D model of architectural and historical mosque facade and comparing the accuracy of using digital commercial non-metric cameras with different resolutions and metric camera with flatbed scanner and photogrammetric scanner for architectural building documentation. El-Nasr Mosque façade in Mansoura city, Egypt was chosen as a case study in this paper. At first, twenty five points were selected at mosque façade at different elevations and distributed at different façade surfaces and observed using total station. Some of these points were selected as control points and the others were selected as check points to validate the results. Effect of control point’s number on image processing and analysis is also studied. Three cameras positions were selected for imaging to get the full details of mosque façade. Close range Digital Workstation (CDW) program was used for processing and analysis of multiple images. The results are indicated that close range photogrammetry using metric camera with photogrammetry scanner instead of flatbed scanner in technique is accurate enough to be beneficial in 3D architectural building documentation. Digital cameras with CRP technique give up different accuracy that depends mainly on the resolution of cameras and camera specifications.

Enhancement of UAV-Aerial Images Using Weighted Differential Evolution Algorithm

Depending on technological developments, the use of Unmanned Aerial Vehicles (UAVs) is increasing day by day and is a valuable source of data for different applications. Generally, low-cost and lightweight non-metric digital cameras are used in UAV systems. During the data collection phase, exposure parameters such as camera shutter speed, aperture value, ISO value, and various weather and light conditions have significant effects on image quality. Image enhancement methods can be used to increase image quality in accordance with the desired purpose. In this study, image enhancement is considered as an optimization problem and Weighted Differential Evolution (WDE) Algorithm is used to solve it. The image quality is enhanced by using an objective function in which performance measures of entropy value, sum of edge density and number of edge pixel are maximized. In the proposed color image enhancement method, aerial images defined in RGB color space are transformed into HSV color space images. the brightness component (V) of HSV color space is modified for image improvement with WDE algorithm. The performance of the proposed method has been compared with other existing techniques such as histogram equalization, linear contrast stretching and evolutionary computing-based image enhancement method like Artificial Bee Colony (ABC) Algorithm in terms of fitness value and image quality.

3D Modeling of Bajang Ratu Temple using UAV Photogrammetry with Oblique Images

The Bajang Ratu Temple is located in Dukuh Kraton, Temon Village, Trowulan District, Mojokerto Regency, East Java, Indonesia, one of the heritage buildings of the Majapahit Kingdom. 3D modeling is one of the efforts that can be used to carry out reconstruction of the Bajang Ratu Temple. In this study, 3D modeling of Bajang Ratu Temple uses a close-range photogrammetry method with low and high oblique images taken using a non-metric camera on the Unmanned Aerial Vehicle. The results of this study were obtained geometric accuracy, that is RMSEx = 0,043 m, RMSEY = 0,049 m, and RMSEZ = 0,092 m for high oblique images. While, for low oblique images, the geometric accuracy are RMSEx = 0,054 m, RMSEY = 0,062 m, and RMSEZ = 0,120 m. The visual analysis results show that the exterior structure of the 3D model formed has resembled the true Bajang Ratu Temple in reality. Based on the shape’s analysis, the 3D model object has an RMSE value of less than 0.5 m, so that it can appropriate the criteria for Level of Detail of order three that is RMSE < 0.5 m.

Comparison of 3D models of an object placed in two different media (air and water) created on the basis of photos obtained with a mobile phone camera

Photogrammetry is one of the contactless geodetic techniques that provide reliable information about objects and their surface properties. Traditional photogrammetric methods require specialized equipment, such as metric cameras, which are very expensive and difficult to access, and the processing of the data obtained from them requires a significant investment of time. An alternative to this solution are generally available non-metric cameras, which can replace professional photogrammetric devices. Currently, consumer-grade digital cameras are enjoying the increase of popularity among photogrammeters thanks to the interchangeable lenses, good image sensor quality and the ability to manually set all camera parameters. However, due to the high costs of purchasing and maintaining such equipment, mobile phone digital cameras are increasingly used, the parameters of which are beginning to match many professional digital SLRs. The newest smartphones are also waterproof, so they can have potential applications in underwater photogrammetry.This article presents the possibilities of using mobile phone cameras in close-range photogrammetry and shows the beginning of research on the use of smartphones in underwater photogrammetry. Three-dimensional models of the gear wheel were made on the basis of photos obtained in two media: in the air and underwater. The two point clouds were then compared, obtaining an average distance difference of ±0,3 mm.

Comparison of Free and Commercial Software in the Processing of Data Obtained from Non-Metric Cameras

Comparison of Free and Commercial Software in the Processing of Data Obtained from Non-Metric Cameras

Optimization of Photogrammetric Flights with UAVs for the Metric Virtualization of Archaeological Sites. Application to Juliobriga (Cantabria, Spain)

Three-dimensional models are required to virtualize heritage sites. In recent years, different techniques that ease their generation have been consolidated, such as photogrammetry with Unmanned Aerial Vehicles (UAVs). Nonmetric cameras allow relatively inexpensive data collections. Traditional aerial photogrammetry has established methodologies, but there are not commonly used recommendations for the selection of parameters when working with UAV platforms. This research applies the Taguchi Design of Experiments Method, with four parameters (height of flight, forward and lateral overlaps, and inclination angle of the sensor) and three levels (L9 matrix and nine flights), to determine the set that offers the best metric goodness and, therefore, the most faithful model. The Roman civitas of Juliobriga (Cantabria, North of Spain) was selected for this experiment. The optimal flight results of the average signal-to-noise ratio analysis were height of 15 m, forward and lateral overlaps of 80%, and inclination of 0° (nadiral). This research also highlights the noticeable contribution of the inclination in the accuracy of the model with respect to the others, which is 16.4 times higher than that of the less relevant one (height of flight). This leads to propose avoiding inclination angle as a variable, and the sole development of nadiral flights to obtain accurate models.

Digital Model in Close-Range Photogrammetry Using a Smartphone Camera

Smartphones recently expanded the potential for low-cost close-range photogrammetry for 3D modeling. They enable the simultaneous collection of large amounts of data for a variety of requirements. It is possible to calculate image orientation elements and triangular coordinates in phases as in Relative and Absolute image orientation. This study demonstrates the photogrammetric 3D reconstruction approach that performs on tablets and smartphones as well. Images are taken with smartphone cameras of iPhone 6 and then calibrated automatically using normal calibration model for photogrammetry and computer vision on a PC, depend on Agisoft Lens add-on that imbedded in Agisoft program, and MATLAB camera calibration Toolbox, and by using an oriented bunch of images of chessboard pattern for large point cloud-based picture using matching. The camera calibration results indicate that the calibration processing routines pass without any error, and the accuracy of estimated IOPs was convenient compared with non-metric digital cameras and are more accurate in Agisoft Lens in terms of standard error. For the 3D model, 435 cameras were used, 428 cameras located from 435 are aligned in two photogrammetric software, Agisoft PhotoScan, and LPS. The number of tie points that are used in LPS is 10 tie points, and 4 control points which used to estimate the EOPs, and the number of tie points that are regenerated in Agisoft PhotoScan were 135.605 points, the number of Dense cloud 3,716,912 points are generated, for 3D model a number of 316,253 faces are generated, after processing the tiled model generated (6 levels, 1.25 cm/pix), the generated DEM having (2136×1774/pix), the dimensions of the generated high-resolution orthomosaic are (5520×4494, 4.47 cm/pix). For accuracy assessment, the Xerr. = 0.292 m, Yerr. = 0.38577 m, Zerr.= 0.2889 m, and the total RMS = 0.563 m in the estimated locations of the exterior orientation parameters.

Measuring Surface and Volume of a Spheroid-Shaped 3D Object from a Single Image

The extraction of accurate geometric measurements from images normally requires the use of metric cameras and stereoscopic observations. However, as good-quality digital cameras are widely available in mobile devices (smartphones, tablets), there is great interest to develop alternative approaches, suitable for these devices. This paper presents a methodology to compute the surface area and volume of a spheroid-shaped object, such as many types of fruit, from a single image acquired by a standard (non-metric) camera and a basic calibration target. An iterative process is used to establish a 3D spheroid out of the observed 2D ellipse, after which auxiliary images of height, resolution and surface area of each pixel on the 3D object surface are created. The method was tested with a data set of 2400 images, of 10 different objects, 2 calibration targets, 2 cameras and 2 mark types. The average relative errors ( $$ $$ ) in establishing the 3D object semi-diameters were 0.863% and 0.791%. The semi-diameters are used to compute the object’s surface area ( $$ $$ = 1.557%) and volume ( $$ $$ = 2.365%). The estimation of the sub-region (mark) surface area over the modelled 3D object resulted in $$ $$ = 2.985%, much lower that what is obtained ignoring the fact that the mark is not on the reference (calibration) plane ( $$ $$ = 50.7%), thus proving the effectiveness of the proposed iterative process to model the 3D object (spheroid).

UAV IMAGING AT RGB FOR CROP CONDITION MONITORING

Abstract. Modern techniques such as precision agriculture tasks are provided to intentional fertilization, pesticide dosing or simply watering the crops. These tasks need to be continuously monitored. One of known method for analyzing the crops conditions is calculating the vegetation indexes. This paper focuses on purpose of using images made with UAV equipped with ordinary non-metric digital RGB camera. The methods had been taken revealed easy to use and cost effective. We present an experiment which attend to distinguish different crops conditions on two test fields sowed with wheat and rape. For this purpose, two different RGB based vegetation indexes were analyzed. The results of calculated indexes shown how crops differs in each stage of vegetation. During the first stage (germinating) the plants are green and average TGI is low. It increases at second stage (flowering) because of plant flowers, which partly cover the leaves. At last stage (ripening) TGI decreases, so plants are still green but starting to dry and change their color.

3D DEFORMATION MEASUREMENT OF CONCRETE WALL USING CLOSE-RANGE PHOTOGRAMMETRY

Abstract. Due to the development of digital image processing, digital photogrammetry is becoming an interesting research area in the field of structural monitoring in civil engineering. This study presents a photogrammetric measurement technique for concrete wall deformation monitoring in the destructive experiment. The non-contact photogrammetric measurement technique which provides surface deformation, is more flexible than the contacted single-point measurement technique (e.g., linear variable displacement transducers, LVDT). The major steps of the proposed scheme include (1) camera calibration, (2) orientation modeling, (3) 3D dense matching, and (4) filtering and interpolation for surface deformation. This experiment used two non-metric digital cameras to measure the deformation of a concrete wall in destructive experiment. The validation compared the image-derived and ranger-derived displacements during the experiment with mean error and standard errors of 32 epochs were −0.02mm and 0.81mm, respectively. The correlation between image-derived displacement and LVDT-derived displacement was 0.9803. The advantage of photogrammetry is to derive surface deformation which covered the whole wall during the experiment. In summary, this study demonstrated that photogrammetry is a useful measurement technique for concrete wall destructive experiment.

AN ITERATIVE APPROACH FOR SELF-CALIBRATING BUNDLE ADJUSTMENT

Abstract. Obtaining accurate image interior and exterior orientations is the key to improve 3D measurement accuracy besides reliable and accurate image matching. A majority of cameras used for those tasks are non-metric cameras. Non-metric cameras commonly suffer various distortions. Generally, there are two ways to remove these distortions: 1) conducting prior camera calibration in a controlled environment; 2) applying self-calibrating bundle adjustment in the application environment. Both approaches have their advantages and disadvantages but one thing is common that there is no universal calibration model available so far which can remove all sorts of distortions on images and systemic errors of image orientations. Instead of developing additional calibration models for camera calibration and self-calibrating adjustment, this paper presents a novel approach which applies self-calibrating bundle adjustment in an iterative fashion: after performing a conventional self-calibrating bundle adjustment, the image coordinates of tie points are re-calculated using the newly obtained self-calibration model coefficients, and the self-calibrating bundle adjustment is applied again in the hope that the remaining distortions and systematic errors will be reduced further within next a few iterations. Using a “virtual image” concept this iterative approach does not require to resample images or/and re-measure tie points during iterations, only costs a few additional iterations computational resource. Several trails under various application environments are conducted using this proposed iterative approach and the results indicate that not only the distortions can be reduced further but also image orientations become much stable after a few iterations.