Line Based Camera Calibration In Machine Vision Dynamic Applications

The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.10210010

Measurement traceability and uncertainty in machine vision applications

During the past decades increasing use of machine vision in dimensional measurements has been seen. From a metrological view every serious measurement should be traceable to SI units and have a stated measurement uncertainty. The first step to ensure this is the calibration of the measurement instruments. Quality systems in manufacturing industry require traceable calibrations and measurements. This has lead to a good knowledge of measurement accuracy for traditional manual hand-held measurement instruments. The entrance of rather complex computerised machine vision instruments and optical coordinate measuring machines, at the production lines and measurement rooms, is a threat or at least a challenge, to the understanding of the accuracy of the measurement. Accuracies of algorithms for edge detection and camera calibration are studied in the field of machine vision, but uncertainty evaluations of complete systems are seldom seen. In real applications the final measurement uncertainty is affected by many factors such as illumination, edge effects, the operator, and non-idealities of the object to be measured. In this thesis the use of the GUM (Guide to the Expression of Uncertainty in Measurement) method is applied for the estimation of measurement uncertainty in two machine vision applications. The work is mainly limited to two-dimensional applications where a gray-scale camera is used. The described equipment for calibration of micrometers using machine vision is unique. The full evaluation of measurement uncertainty in aperture diameter measurements using an optical coordinate measuring machine is presented for the first time. In the presented applications the uncertainty budgets are very different. This confirms the conclusion, that a detailed uncertainty budget is the only way to achieve an understanding of the reliability of dimensional measurements in machine vision. Uncertainty budgets for the type of the two described machine vision applications have never previously been published.Viime vuosikymmenien aikana konenäkö on yleistynyt yhä enemmän geometrisissä mittauksissa. Metrologisesta näkökulmasta jokaisen mittauksen olisi oltava jäljitettävissä SI-yksikköjärjestelmään ja jokaisella mittauksella tulisi olla tunnettu mittausepävarmuus. Kaupallisesta näkökulmasta on tärkeää, että tavaran mitattavista ominaisuuksista ei synny mittausvirheistä johtuvia kiistoja ostajan ja myyjän välillä. Jos mittausepävarmuus on tunnettu, niin kalibroinnilla saadaan aikaan jäljitettävyys perussuureeseen. Jäljitettävyys konenäkösovelluksissa pituuden SI-yksikköön metriin saadaan aikaan pitkällä katkeamattomalla jäljitettävyysketjulla. Konepajoissa laatujärjestelmät ovat jo pitkään edellyttäneet, että mittalaitteet ovat jäljitettävästi kalibroitu. Jokaiseen kalibrointiin liittyy myös mittausepävarmuuslaskelma, jossa tärkeimmät epävarmuuslähteet ovat mallinnettu. Optisten koordinaattimittauskoneiden sekä muiden konenäköön perustuvien mittausjärjestelmien mutkikkuus on suuri haaste mittausepävarmuuslaskelman laatimiselle. Konenäkö sekä tarkkuuskysymykset konenäössä ovat paljon tutkittuja aiheita, mutta kokonaisten mittausjärjestelmien epävarmuuslaskelmia laaditaan edelleenkin erittäin harvoin. Epävarmuustekijöitä, jotka olisi otettava huomioon, ovat valaistuksen, reunojen ja käyttäjän valintojen vaikutus yhdessä mitattavan kappaleen mahdollisten puutteellisuuksien kanssa. Tässä työssä tutkitaan GUM-menetelmän (Guide to the Expression of Uncertainty in Measurement) käyttöä kolmessa konenäkösovelluksessa, joille esitetään epävarmuuslaskelma. Neljäs esitettävä sovellus on apertuurien halkaisijan mittaaminen optisella koordinaattimittauskoneella. Ensimmäistä kertaa tällaiselle sovellukselle esitetään mittausepävarmuuslaskelma. Työn johtopäätöksenä on, että yksityiskohtaisen epävarmuuslaskelman laatiminen on ainut keino saada käsitys mittauksen virhelähteistä. Työ on rajattu kaksidimensionaalisiin mittauksiin, joissa käytetään yhtä harmaasävykameraa.reviewe

Theory and development of a camera-based noncontact vibration measurement system

Title from PDF of title page; abstract from research PDF (University of Missouri--Columbia, viewed on June 25, 2014).Dramatic advancement in technologies for high-speed high-resolution digital cameras in recent years enables the development of camera-based full-field noncontact measurement systems for vibration testing of flexible multibody systems undergoing large rigid-body motion and elastic/plastic deformations. A few of such systems exist in today's metrology market, but they are inconvenient for use and prohibitively expensive. Most seriously, they are not really appropriate for structural vibration testing because their measurement accuracy is low due to several technical reasons, including inappropriate setting of cameras and experimental setup because of user's innocence of video-grammetry, non-precise corner detection and other problems of image processing techniques, and inaccurate modeling and calibration of cameras. This thesis develops and puts together a complete set of necessary techniques for the development of a camerabased noncontact full-field vibration measurement system using inexpensive off-the-shelf digital cameras. An optimal combination of appropriate methods for corner detection, camera calibration, lens distortion modeling, and measurement applications is proposed and numerically and experimentally verified. Moreover, we derive/improve some image processing methods and 3D reconstruction algorithms to improve vibration measurement accuracy. The proposed methods include: 1) a corner detection method for processing 2D images with sub-pixel resolutions, 2) an improved flexible camera calibration method for easy and fast calibration with high accuracy, 3) a lens distortion model for correcting radial, decentering, and thin prism distortions, 4) a set of guidelines for setting up cameras and experiments for measurement, and 5) algorithms for measurement applications. The proposed corner detection method improves Foerstner's corner detector, which improved Moravec's and Harris's corner detectors. The proposed camera calibration method improves Zhang's flexible technique, which works without knowing the object's 3D geometry or computer vision. The method only requires the camera to observe a planar pattern (e.g., a checker board) shown at two or more independent orientations by arbitrarily moving the planar pattern (or the camera). Estimation of the camera's intrinsic parameters (i.e., focal length, principal point, the skewness parameter and aspect ratios of the two image axes, and lens distortion parameters) and extrinsic parameters (i.e., camera's location and orientation with respect to the referential world coordinate system) consists of an approximate initial guess based on linear closed-form solutions and then nonlinear optimization for refinement. This approach is between the photogrammetric calibration and the self-calibration. Compared with photogrammetric calibration techniques that use expensive calibration objects of two or three orthogonal planes, the proposed technique is easy to use and flexible. To examine the proposed methods and their combined effects against high measurement accuracy, two Canon EOS-7D DSLR cameras are used for theoretical studies and experimental verifications. Numerical and experimental results show that the recommended methods together with our improved image processing techniques is feasible for the development of a camera-based noncontact full-field vibration measurement system with high precision and low cost. This camera-based measurement instrument has the potential for developing new structural testing techniques and can open new possibilities for research and development in mechanical and aerospace engineering, computer science, animal science, and many other fields

Epipolarización de un par fotogramétrico sin parámetros de orientación

La reconstrucción de escenas mediante procesamiento de imagen resulta un trabajo habitual en fotogrametría. En aquellos casos que requieran 2D, el procesamiento de imágenes aisladas puede resultar suficiente, mientras que la generación de escenas 3D requiere del uso de múltiples imágenes. Una técnica habitual de trabajo para generar escenas 3D es la epipolarización. Habitualmente estas técnicas requieren del uso de parámetros de orientación interna, lo que implica la calibración de la/s cámara/s. Así mismo, también resulta necesario conocer la orientación relativa entre los fotogramas. En este trabajo se presenta un algoritmo completamente geométrico que permite la generación de diferentes modelos 3D, con un único par fotogramétrico, sin ningún parámetro de orientación y sin preseñalización de puntos de control. El algoritmo permite la generación de modelos 3D con imágenes provenientes de cámaras desconocidas, escaneadas de un libro o video frames. Los modelos 3D obtenidos están libres de paralajes y presentan un ajuste mejor a 0,5 pixels

Stereoskopische Korrespondenzbestimmung mit impliziter Detektion von Okklusionen

Der Einsatz binokularer Sehsysteme eröffnet sowohl in der Natur als auch in der Technik die Möglichkeit zum räumlichen Sehen.Das Grundprinzip bildet hierbei eine passive Triangulation, deren Ausgangspunkte die korrespondierenden Positionen darstellen, auf die ein Raumpunkt in die Stereobilder projiziert wird. Das zentrale Problem besteht bei dieser Technik darin, die korrespondierenden Bildpunkte eindeutig einander zuzuordnen. Dieses sogenannte Korrespondenzproblem ist einerseits aufgrund mehrerer ähnlicher Strukturen in der betrachteten Szene oft stark mehrdeutig und besitzt andererseits nicht immer eine Lösung, da Bereiche in der Szeneauftreten können, die nur aus einer der beiden Perspektiven zusehen sind. Weiterhin wird eine eindeutige Zuordnung korrespondierender Bildbereiche durch interokuläre Differenzen wie perspektivische Verzerrungen, Beleuchtungsunterschiede und Rauschprozesse zusätzlich erschwert. In der vorliegenden Arbeit werden die einzelnen Komponenten eines Gesamtsystems vorgestellt, die zur stereoskopischen Rekonstruktion der räumlichen Struktur einer Szene erforderlich sind. Den Schwerpunkt der Arbeit bildet ein Selbstorganisationsprozeß, der in Verbindung mit weiteren Verfahrensschritten eine eindeutige Zuordnung korrespondierender Bildpunkte erlaubt. Darüber hinaus werden hierbei einseitig sichtbare Bildbereiche, die eine wesentliche Fehlerursache in der Stereoskopie darstellen, detektiert und vom Zuordnungsprozeß ausgeschlossen.Stereo vision is a passive method used to recover the depth information of a scene, which is lost during the projection of a point in the 3D-scene onto the 2D image plane. In stereo vision, in which two or more views of a scene are used, the depth information can be reconstructed from the different positions in the images to which a physical point in the 3D-scene is projected. The displacement of the corresponding positions in the image planes is called disparity. The central problem in stereo vision, known as the correspondence problem, is to find corresponding points or features in the images. This task can be an ambiguous one due to several similar structures or periodic elements in the images. Furthermore, there may be occluded regions in the scene, which can be seen only by one camera. In these regions there is no solution for the correspondence problem. Interocular differences such as perspective distortions, differences in illumination and camera noise make it even more difficult to solve the correspondence problem. The main focus of this work is a new stereo matching algorithm, in which the matching of occluded areas is suppressed by a self-organizing process. In the first step the images are filtered by a set of oriented Gabor filters. A complex valued correlation-based similarity measurement, which is applied to the responses of the Gabor filters, is used in the second step to initialize a self-organizing process. In this self-organizing network, which is described by coupled, non-linear evolution equations, the continuity and the uniqueness constraints are established. Occlusions are detected implicitly without a computationally intensive bidirectional matching strategy.von Dipl.-Ing. Ralph Trapp aus Winterberg. Referent: Prof. Dr. rer. nat Georg Hartmann, Korreferent: Prof. Dr.-Ing. Ulrich RückertTag der Verteidigung: 15.09.1998Universität Paderborn, Univ., Dissertation, 199

Contributions to image-based object reconstruction : geometric and photometric aspects

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Caracterización y optimización del proceso de calibrado de cámaras basado en plantilla bidimensional

El procedimiento de calibrado de una cámara acaba siendo un paso necesario para la obtención de información 3D del entorno a partir de imágenes 2D del mismo. Existen diferentes técnicas las cuales se basan en fotogrametría o autocalibración. Los métodos basados en fotogrametría capturan una imagen de una escena conocida compuesta por una plantilla tridimensional, bidimensional o unidimensional. Las técnicas de auto calibración se basan en la obtención de varias imágenes de una misma escena aprovechando la rigidez de la misma para establecer restricciones que permitan realizar la calibración de la cámara. Como resultado de la calibración de la cámara se obtienen los parámetros intrínsecos y extrínsecos de la misma. La obtención de todos los parámetros de la cámara mediante calibración, no es exacta debido a imprecisiones que perturban el proceso. Estas imprecisiones surgen por imperfecciones constructivas de las lentes, desalineamientos mecánicos de las mismas o del sensor, y también por procesar la imagen y obtener posiciones de los puntos dentro de ellas. Los resultados dependen tanto de la plantilla de calibración utilizada, como del algoritmos para resolverla, así como del tratamiento previo que se les pueda realizar a los datos. Desde el punto de vista que es imposible obtener una valor exacto para cada uno de los parámetros de la cámara, resulta interesante obtener un intervalo. Estas incertidumbres asociadas a los parámetros de la cámara permitirán mejorar los procedimientos de reconstrucción 3D y de medida que se realicen a partir de los mismos. También, a la hora de calibrar una cámara surgen preguntas acerca del algoritmo o plantilla a utilizar, nº de puntos a colocar en la plantilla, nº de imágenes a tomar de la misma, así como las posiciones y orientaciónes desde las que tomar las imágenes. Esta tesis pretende dar respuesta a todas estas cuestiones. En primer lugar se adopta el método de calibración que mejor resultados obtiene basándose en los métodos eRicolfe Viala, C. (2006). Caracterización y optimización del proceso de calibrado de cámaras basado en plantilla bidimensional [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1858Palanci