Automatic Measurement of Circular Artificial Targets in Digital Image

A novel approach is presented for the location of discrete targets images with subpixel accuracy. It can be adopted as first stage of any method that uses planar and no-planar grids with circular, square or cross shaped targets in order to calibrate close range cameras. The approach has been performed on several calibration sessions each of them followed by the three-dimensional reconstruction of a reference object that was previously measured through a coordinate measuring machine. The performance of the proposed approach has been expressed in terms of deviation between the reference coordinates and the corresponding ones provided by triangulation. The results obtained have also been compared with those achieved through ShapeCapture^TM, a software widely used in photogrammetry for camera calibration and 3D model reconstruction from images.

Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds

Stereometry in very close-range stereophotogrammetry with non-metric cameras for human movement analysis

Glacier roughness at sub-metre scales is an important control on the ice surface energy balance and has implications for scattering energy measured by remote-sensing instruments. Ice surface roughness is dynamic as a consequence of spatial and temporal variation in ablation. To date, studies relying on singular and/or spatially discrete two-dimensional profiles to describe ice surface roughness have failed to resolve common patterns or causes of variation in glacier surface morphology. Here we demonstrate the potential of close-range digital photogrammetry as a rapid and cost-effective method to retrieve three-dimensional data detailing plot-scale supraglacial topography. The photogrammetric approach here employed a calibrated, consumer-grade 5 Mpix digital camera repeatedly imaging a plot-scale (≤25 m2) ice surface area on Midtre Lovénbreen, Svalbard. From stereo-pair images, digital surface models (DSMs) with sub-centimetre horizontal resolution and 3 mm vertical precision were achieved at plot scales ≤4 m2. Extraction of roughness metrics including estimates of aerodynamic roughness length (z0) was readily achievable, and temporal variations in the glacier surface topography were captured. Close-range photogrammetry, with appropriate camera calibration and image acquisition geometry, is shown to be a robust method to record sub-centimetre variations in ablating ice topography. While the DSM plot area may be limited through use of stereo-pair images and issues of obliquity, emerging photogrammetric packages are likely to overcome such limitations.

In image-based measurements, quantitative image data must be mapped to three-dimensional object space. Analytical photogrammetric methods, which may be used to accomplish this task, are discussed from the viewpoint of experimental fluid dynamicists. The Direct Linear Transformation (DLT) for camera calibration, used in pressure sensitive paint, is summarized. An optimization method for camera calibration is developed that can be used to determine the camera calibration parameters, including those describing lens distortion, from a single image. Combined with the DLT method, this method allows a rapid and comprehensive in-situ camera calibration and therefore is particularly useful for quantitative flow visualization and other measurements such as model attitude and deformation in production wind tunnels. The paper also includes a brief description of typical photogrammetric applications to temperature- and pressure-sensitive paint measurements and model deformation measurements in wind tunnels.

Direct Linear Transformation from Comparator Coordinates into Object Space Coordinates in Close-Range Photogrammetry

There are the geometric heterogeneity in different shapes of mouldboard ploughs. In order to evaluate the accuracy in measuring the 3D coordinates, and to study the simple mathematical surface which best fits the actual surface of the mouldboard plough, low-cost close-range photogrammetry were used for calculation of the 3D coordinates by co-linearity equation and direct linear transformation, which shoot the two image of 193 targets point marked on the model surface, and carry out binocular stereo matching according to the parallax factor. The results obtained indicate that the surface of a mouldboard plough can be shaped with an accuracy of approximately 1.3 mm, the 3D coordinates of 193 points on the surface of a plough are measured with great accuracy (root mean square 0.66 mm), with the adjustment of a cubic polynomial surface to just 25 control points randomly distributed over the surface of the plough. this surface can be applied to the theoretical analysis of the working process and the manufacture of the mouldboard plough.

An improved outdoor camera calibration method based on Extended Kalman Filter (EKF) is proposed in this paper. GPS coordinate system is introduced to establish world coordinate system in the calibration procedure. According to the characteristics of GPS coordinate converted to plane coordinate and the camera calibration model, we establish the mapping relations of reference points between image plane coordinate and the world coordinate. Further, we consider the world coordinate error, set the world coordinates as the measure quantities, use the method of EKF to get the optimal estimation of intrinsic and extrinsic camera parameters, in EKF the camera's intrinsic and extrinsic parameters are set as state variables, the transformation equations of image coordinate to the world coordinate are set as the measurement equations, and we let the observed feature points' image coordinates and corresponding world coordinates as the input of the filter. Experimental results confirmed that the proposed method with high precision. Index Terms - camera calibration, GPS coordinate, EKF, world coordinate error

Today, non-metric cameras are used wide-spread in close-range photogrammetric applications. Such professional cameras can be combined with both digital and mechanical zooming satisfactorily. Optical behavior of the lenses is changed depending on the feature of the optical system used during the zooming process. This so-called change is arranged by optimizing the number of pixels used on the digital sensor, on the projection plane. The problem of high definition, digital, non-metric professional cameras is that while sharpening the image, it deteriorates the definition of the image plane. Industrial cameras, which are used in industrial production, can overcome this problem by using additional image enhancement instruments. These digital non-metric cameras, which are generally used in close-range photogrammetry and in architectural photogrammetry, are calibrated by fixing for maximum and minimum zooming focal length and they are suitable to be used in this range. In this study, an Olympus E10 camera is calibrated to meet the need for the modification, for different focal lengths. Its calibration data, which is obtained in 3D test field, together with the distortions on the object, is used to detect the optical behavior of zooming object for mechanic zooming. Key words: Camera calibration, zoom lens distortion, close range photogrammetry, parameter estimation, parameter analysis.

The conventional calibration methods based on a perspective camera model are not suitable for the underground camera with two-layer glasses, which is specially designed for explosion proof and dust removal in a coal mine. Underground camera modeling and calibration algorithms are urgently needed to improve the precision and reliability of underground visual measurement systems. This article presents a novel geometrically driven underground camera calibration algorithm for a boom-type roadheader. The underground camera model is established under coplanarity constraints, considering explicitly the impact of refraction triggered by the two-layer glasses and deriving the geometrical relationship of equivalent collinearity equations. On this basis, we perform parameters calibration based on a geometrically driven calibration model, which are 2D-2D correspondences between the image points and object coordinates of the planar target. A hybrid Levenberg-Marqurdt (LM) and particle swarm optimization (PSO) algorithm is further proposed in terms of the dynamic combination of the LM and PSO, which optimizes the underground camera calibration results by minimizing the error of the nonlinear underground camera model. The experimental results demonstrate that the pose errors caused by the two-layer glass refraction are well corrected by the proposed method. The accuracy of the cutting-head pose estimation has increased by 55.73%, meeting the requirements of underground excavations.

This paper describes a mathematical model for automatic registration of digital images of sting-mounted test articles in aerodynamic test facilities. The model is based on three premises: the use of registration targets on the test article; approximate knowledge of the attitude angles of the test article with respect to the test facility at each measurement point; and the ability to calibrate the cameras with respect to the test facility. Registration of individual images proceeds in three steps: initial predictions are calculated for the image coordinates of all visible registration targets; template-based searches are performed to locate the targets to subpixel accuracy; and lastly, an exact mapping between 2D image coordinates and 3D model coordinates is established. The math model includes deflection of the sting under air loads. Sample results are presented for several wind tunnel tests.

For line structured light vision sensor in robotic eye-in-hand system, the calibration of camera parameters, robot hand eye parameters and structured light plane parameters is an indispensable procedure before conducting 3-D measurement. Traditionally, these three sets of parameters are calibrated separately, making the calibration process complicated and inefficient. To address this, an efficient calibration method is proposed in this paper. By changing the poses of robot and calibration target, a set of images of the calibration target is captured, upon which the camera calibration is conducted. The extrinsic parameters obtained from camera calibration are utilized in the calibration of the structured light plane parameters and hand eye parameters, using the same set of images. Therefore, the three sets of parameters can be simultaneously calibrated with simple on-site operations. Moreover, the calibration target used in this method is only a planar checkerboard, which can be easily acquired at low cost. It is verified in the experiment that the proposed method is efficient and accurate, with the calibration duration within 10 minutes and the measurement accuracy within 0.40mm. Additionally, object pose measurement experiment is conducted to validate the effectiveness of the proposed method in practical application.

Camera calibration is a critical prerequisite for precision optical measurement systems. Traditional methods predominantly rely on either chessboard or circular calibration targets, each exhibiting inherent limitations. Chessboard targets facilitate straightforward corner detection but suffer from relatively low localization accuracy. Circular targets enable high-precision center extraction but are susceptible to systematic errors induced by perspective distortion, which causes the projected ellipse center to deviate from the true physical circle center (eccentricity error). To overcome these limitations, this paper introduces a high-precision camera calibration method that leverages a novel, to our knowledge, hybrid calibration board embedding circular markers within a chessboard pattern. The proposed approach first detects readily detectable chessboard corners to compute a homography matrix, which rectifies local image regions parallel to the imaging plane, thereby transforming the elliptical marker projections into approximately circular shapes. The centers of these corrected markers are accurately extracted using image moments. Subsequently, an inverse perspective transformation projects the centers back to the original image plane to obtain their precise pixel coordinates, effectively mitigating the perspective-induced eccentricity error. Camera calibration is then performed using Zhang's method with the refined coordinates. Extensive experiments demonstrate that the proposed method achieves an average reprojection error of 0.0365 pixels, representing a significant improvement of 51.13% compared to the traditional chessboard pattern and 35.05% compared to the circle pattern.

Construction of high-speed railway in China has entered a period of rapid growth. To accurately and quickly obtain the dynamic envelope curve of high-speed vehicle is an important guarantee for safe driving. The measuring system is based on binocular stereo vision. Considering the difficulties in field calibration such as environmental changes and time limits, carried out a field calibration method based on fast reconstruction of three-dimensional control field. With the rapid assembly of pre-calibrated three-dimensional control field, whose coordinate accuracy is guaranteed by manufacture accuracy and calibrated by V-STARS, two cameras take a quick shot of it at the same time. The field calibration parameters are then solved by the method combining linear solution with nonlinear optimization. Experimental results showed that the measurement accuracy can reach up to ± 0.5mm, and more importantly, in the premise of guaranteeing accuracy, the speed of the calibration and the portability of the devices have been improved considerably.

Developed and tested for many years, a variety of tumor hypoxia detection methods have been inconsistent in their ability to predict treatment outcomes or monitor treatment efficacy, limiting their present prognostic capability. These variable results might stem from the fact that these approaches are based on inherently wide-ranging global tumor oxygenation levels based on uncertain influences of necrotic regions present in most solid tumors. Here, we have developed a novel non-invasive and specific method for tumor vessel hypoxia detection, as hypoxemia (vascular hypoxia) has been implicated as a key driver of malignant progression, therapy resistance and metastasis. This method is based on high-frequency ultrasound imaging of α-pimonidazole targeted-microbubbles to the exogenously administered hypoxia marker pimonidazole. The degree of tumor vessel hypoxia was assessed in three mouse models of mammary gland carcinoma (4T1, SCK and MMTV-Wnt-1) and amassed up to 20% of the tumor vasculature. In the 4T1 mammary gland carcinoma model, the signal strength of α-pimonidazole targeted-microbubbles was on average 8-fold fold higher in tumors of pimonidazole-injected mice than in non-pimonidazole injected tumor bearing mice or non-targeted microbubbles in pimonidazole-injected tumor bearing mice. Overall, this provides proof of principle for generating and targeting artificial antigens able to be ‘created’ on-demand under tumor specific microenvironmental conditions, providing translational diagnostic, therapeutic and treatment planning potential in cancer and other hypoxia-associated diseases or conditions.