This paper addresses methods for statistical uncertainty analysis to determine the measurement accuracy associated
with a video-extensometer system. Two different approaches for statistical uncertainty analysis - a purely
statistical and an analytical approximation - are presented. The statistical method is based on evaluation of
images acquired at conditions of repeatability; whereas the analytical approach consists of application of the law
of first order error propagation to the particular processing steps of the evaluation procedure.
The derivation of the law of first order error propagation is briefly revised in order to emphasize possible
sources of error caused by its application. Moreover, the computation of the Jacobian matrix required for first
order approximations of error propagation is illustrated for explicit and implicit vector-valued functions as well
as for linear least squares problems as this represents a task typically arising in metric vision applications.
Finally, the two approaches are applied to the specific processing steps for the evaluation of the images
acquired with the video-extensometer system. Comparison of the results obtained with the different methods
show negligible deviations, proving the application of the law of first order error propagation to be a suitable
means to analytically estimate statistical uncertainty.
KEYWORDS: RGB color model, Cameras, Image processing, Calibration, 3D modeling, Control systems, Scanners, 3D image processing, Imaging systems, Image segmentation
The surface machining of cracks is a key issue to ensure the quality of steel rods and billets. The aim is to grind these defects out of the material. This paper presents a real-time optical servo-system, consisting of three image processing systems and an industrial robot, which fully automate this process. A high resolution color progressive scan camera, placed at a suitable position above the roller conveyor, observes the material and detects color markings indicating the presence of a crack. This camera system controls the roller conveyor transporting the material until a marked crack is detected. Diffuse light sources provide homogeneous lighting to ensure reliable detection of the markings. A demosaicing algorithm, RGB to HSL color modeling and thresholding with statistical morphology are used to identify the marked areas. On detecting a crack the material is automatically positioned within the working area of an industrial robot. A collineation is used to generate metric two-dimensional coordinates corresponding to the bounding rectangle of the detected error. At this point two plane-of-light scanners are used to acquire a cross section of the material to the left and the right of the robot's working area. From this, a three-dimensional model for the rod or billet surface is calculated and the two-dimensional coordinates of the color marking are projected onto this surface to generate a patch. The coordinates of this patch are sent to the 6R industrial robot, which then grinds out the defect. A new concept has been implemented which enables the calibration of the three image processing systems and the industrial robot so as to have one common coordinate system. Operational results have shown the full functionality of the system concept in the harsh environment of a steel production facility.
This paper presents a digital image processing system for the measurement of the volumetric tensile properties of polymer materials. The standard measurement setup with a single camera system focussing the face of the samples under test is described. An algorithm for fitting parallel and/or orthogonal lines based on singular value decomposition is explained in detail. Applications where higher resolution and accuracy is desired, are addressed by extending the standard measurement setup to two camera systems, whose images can be acquired simultaneously. The non-overlapping fields of view require determination of the relative location of the camera systems. A calibration target and procedure is presented to solve this referencing task. Three-dimensional specimens are subject to motion in testing machines with flexible jaws. An extended hardware setup with two line-projecting lasers is introduced, that enables the measurement of the specimen motion and with this the elimination of the associated errors. In a calibration procedure, the relative locations of the lasers and the camera are determined. The image processing task is extended to calculate the three-dimensional specimen location in each step of the sequence based on the results of the calibration. As a consequence, deformations are determined on the specimen surface under the assumption that the material remains planar. Finally, a number of measurement results gained with the video-extensometer system at real experiments in a testing laboratory are presented and different evaluation algorithms are compared.
The motivation for this work arises from the need for a contactless extension measurement system to obtain material properties of refractories at elevated temperatures of up to 1400°C. There is a lack of tactile probes capable of performing reliable measurements at this temperature range. Presently, the deformation of the specimen is estimated by measuring the movement of the testing machine. To determine material properties such as the modulus of elasticity more accurate information about the real deformation is required. This work presents an optical arrangement and mechanical setup for image acquisition at high temperatures and at a high degree of thermal radiation. Furthermore, an efficient and stable image processing algorithm based on edge detection and line fitting using singular value decomposition is presented. Subsequently the sources of measurement errors are determined and examined. The accuracy of the measurement result is estimated.
(TCP/IP) based, anonymous communication environment is introduced. The main system capabilities are central configurability and maintainability of the image processing nodes and the scalability of the framework. Furthermore a watchdog concept and IEC61131 conform signal integration comprising the Modbus/TCP protocol are integrated within the framework. A communication structure based on the tuplespace concept is presented. The possibility of integrating heterogeneous nodes is achieved by a consistent JavaTM implementation. As a proof of concept, a quality observation task at distributed observation points at a wire rolling mill is introduced. An image-processing algorithm based on least-squares fitting of parallel lines to observe quality relevant parameters is introduced and integrated as an exemplary machine vision implementation within the framework.
This paper presents a prototype system to monitor a hot glowing wire during the rolling process in quality relevant aspects. Therefore a measurement system based on image vision and a communication framework integrating distributed measurement nodes is introduced. As a technologically approach, machine vision is used to evaluate the wire quality parameters. Therefore an image processing algorithm, based on dual Grassmannian coordinates fitting parallel lines by singular value decomposition, is formulated. Furthermore a communication framework which implements anonymous tuplespace communication, a private network based on TCP/IP and a consequent Java implementation of all used components is presented. Additionally, industrial requirements such as realtime communication to IEC-61131 conform digital IO’s (Modbus TCP/IP protocol), the implementation of a watchdog pattern and the integration of multiple operating systems (LINUX, QNX and WINDOWS) are lined out. The deployment of such a framework to the real world problem statement of the wire rolling mill is presented.
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