Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.Comment: 9 pages, 5 figures Corrected errors in equation 1

Medición indirecta de radiación por procesamiento digital de imágenes de luminancia. Resultados preliminares

En el presente trabajo se describe un método para determinar las curvas iso radiación en una superficie plana, cubriendo la misma con un papel blanco, y empleando una cámara digital para obtener una imagen de luminancia. Procesando esta imagen y en base a una distribución de las mismas puede obtenerse una imagen de la radiación sobre este plano. El método requiere, para poder ser cuantificado de la determinación de un punto de referencia de radiación. Por otra parte, se requiere calibrar la cámara con diferentes niveles de radiación. Estos son generados artificialmente con diferentes superficies reflectivas sobre un fondo blanco, consiguiéndose así las distintas escalas de grises. La medición de la radiación incidente en este calibrador, se realiza por métodos convencionales. El dispositivo permite medir distribuciones inhomogéneas de radiación en superficies planas como ser el caso de muros, colectores, cocinas, etc; y cualquier otro tipo de superficies planas, donde se pueda ubicar un fondo blanco, que por razones tales como reflexiones, o incidencia de radiaciones de valor desconocido, tengan distribuciones no uniformes de radiación.A method to fit iso radiation curves over a flat surface is described in the present paper. The surface is covered with a white paper and a digital camera is used in order to obtain a luminance figure. By the processing of the figure is possible to get the radiation image over this plane. Previously, it is necessary to know a reference point of radiation and to calibrate the camera with different levels of radiation. The mentioned radiation levels are artificially generated with different reflective surfaces over a white bottom, so a gray scale is obtained. The incident radiation on the calibrator device is measured by conventional methods. Inhomogeneous distributions of radiation can be measured on flat surfaces like walls, collectors, kitchens, etc., as well as on any flat surface which is able to support a white bottom.Tema 8: Evaluación energética, instrumentación y materiales usados en energías renovables, modelización y simulación.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

Medición indirecta de radiación por procesamiento digital de imágenes de luminancia. Resultados preliminares

En el presente trabajo se describe un método para determinar las curvas iso radiación en una superficie plana, cubriendo la misma con un papel blanco, y empleando una cámara digital para obtener una imagen de luminancia. Procesando esta imagen y en base a una distribución de las mismas puede obtenerse una imagen de la radiación sobre este plano. El método requiere, para poder ser cuantificado de la determinación de un punto de referencia de radiación. Por otra parte, se requiere calibrar la cámara con diferentes niveles de radiación. Estos son generados artificialmente con diferentes superficies reflectivas sobre un fondo blanco, consiguiéndose así las distintas escalas de grises. La medición de la radiación incidente en este calibrador, se realiza por métodos convencionales. El dispositivo permite medir distribuciones inhomogéneas de radiación en superficies planas como ser el caso de muros, colectores, cocinas, etc; y cualquier otro tipo de superficies planas, donde se pueda ubicar un fondo blanco, que por razones tales como reflexiones, o incidencia de radiaciones de valor desconocido, tengan distribuciones no uniformes de radiación.A method to fit iso radiation curves over a flat surface is described in the present paper. The surface is covered with a white paper and a digital camera is used in order to obtain a luminance figure. By the processing of the figure is possible to get the radiation image over this plane. Previously, it is necessary to know a reference point of radiation and to calibrate the camera with different levels of radiation. The mentioned radiation levels are artificially generated with different reflective surfaces over a white bottom, so a gray scale is obtained. The incident radiation on the calibrator device is measured by conventional methods. Inhomogeneous distributions of radiation can be measured on flat surfaces like walls, collectors, kitchens, etc., as well as on any flat surface which is able to support a white bottom.Tema 8: Evaluación energética, instrumentación y materiales usados en energías renovables, modelización y simulación.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

Modeling and Analysis of Soft-Test/Repair for CCD-Based Digital X-Ray Systems

Modern X-ray imaging systems evolve toward digitization for reduced cost, faster time-to-diagnosis, and improved diagnostic confidence. For the digital X-ray systems, charge coupled device (CCD) technology is commonly used to detect and digitize optical X-ray image. This paper presents a novel soft-test/repair approach to overcome the defective pixel problem in CCD-based digital X-ray systems through theoretical modeling and analysis of the test/repair process. There are two possible solutions to cope with the defective pixel problem in CCDs: one is the hard-repair approach and another is the proposed soft-test/repair approach. Hard-repair approach employs a high-yield, expensive reparable CCD to minimize the impact of hard defects on the CCD, which occur in the form of noise propagated through A/D converter to the frame memory. Therefore, less work is needed to filter and correct the image at the end-user level while it maybe exceedingly expensive to practice. On the other hand, the proposed soft-test/repair approach is to detect and tolerate defective pixels at the digitized image level; thereby, it is inexpensive to practice and on-line repair can be done for noninterrupted service. It tests the images to detect the detective pixels and filter noise at the frame memory level and caches them in a flash memory in the controller for future repair. The controller cache keeps accumulating all the noise coordinates and preprocesses the incoming image data from the A/D converter by repairing them. The proposed soft-test/repair approach is particularly devised to facilitate hardware level implementation ultimately for real-time telediagnosis. Parametric simulation results demonstrate the speed and virtual yield enhancement by using the proposed approach; thereby highly reliable, yet inexpensive, soft-test/repair of CCD-based digital X-ray systems can be ultimately realized

Calibration Radiométrique de Caméra

Projet SYNTIMIn Computer Vision methods such as shape-from-shading, 3D reconstruction by correlation and edge detection, all the pixels of the CCD matrix are assumed equivalent. A radiometric camera calibration step is necessary to verify this hypothesis, which is the subject of this paper. First, the modeling of the sensor, based on its physical properties, is described. A method to estimate the parameters of this model is given and the results of experimentations are described. These experiments valid the complete model only partially, and simplifications of this model are subsequently proposed which remain experimentally correct with focal length variations. Finally, improvements of the image analysis process after performing radiometric calibration are demonstrated.La correction des défauts de la radiométrie de la caméra est importante pour vérifier l'hypothèse de similarité des cellules CCD faite dans de nombreuses méthodes d'analyse d'images comme le shape-from-shading, la reconstruction par corrélation et l'extraction de contours. Nous décrivons la modélisation de ces défauts radiométriques à partir de la physique du senseur. Les paramètres de ce modèle peuvent être estimés par différentes expérimentations que nous avons réalisées sur notre objectif, ce qui a permis de partiellement valider le modèle et d'en proposer un autre simplifié, qui reste valide expérimentalement pour un objectif à focale variable. Enfin, les avantages de la correction radiométrique sont illustrés sur différents processus d'analyse d'image

Automatic calibration and removal of distortion from scenes of structured environments

International audienceMost algorithms in 3D computer vision rely on the pinhole camera model because of its simplicity, whereas video optics, especially low-cost wide-angle lens, generate a lot of nonlinear distortion which can be critical. To find the distortion parameters of a camera, we use the following fundamental property: a camera follows the pinhole model if and only if the projection of every line in space onto the camera is a line. Consequently, if we find the transformation on the video image so that every line in space is viewed in the transformed image as a line, then we know how to remove the distortion from the image. The algorithm consists of first doing edge extraction on a possibly distorted video sequence, then doing polygonal approximation with a large tolerance on these edges to extract possible lines from the sequence, and then finding the parameters of our distortion model that best transform these edges to segments. Results are presented on real video images, compared with distortion calibration obtained by a full camera calibration method which uses a calibration grid

Evaluation Method for Automotive Stereo-Vision Systems

International audienceSafe vehicle guidance under human or computer control requires a thorough understanding of the traversed environment. Consequently if perception systems are to be introduced into mass market vehicles as part of driving assistance systems, their proper operation throughout the vehicle working life is needed. Onboard stereo-vision systems can provide rich information in terms of range, feature recognition, etc., hence the interest by car OEMs. System performance depends on multiple factors like light conditions, algorithms and the mechanical apparatus. Due to inaccuracies produced by changes in the system physical properties due to vibrations, misalignment of fixtures, etc. through the vehicle operational life a reduction in performance will occur. In this paper, an evaluation framework to estimate the performance of a vehicle onboard stereo-vision system in terms of 3D measurements and re-projection errors is presented. The approach considers changes that might occur in the system during the vehicle working life. It includes means to evaluate the self-calibration process often used to correct the effects of physical changes in the stereo-vision system. The results provide key information for the design and geometrical specification of automotive stereo-vision systems. As the potential physical changes in the geometric configuration of the camera-pair over the vehicle life time are difficult to predict, it was necessary to simulate them to generate families of errors that these might trigger on the system performance

Ellipse-based camera calibration

An important task in most 3D vision systems is camera modeling . We present a calibration method designed for a good accuracy in the parameters estimation . Accurate image measurments are required to perform the camera model estimation. We suggest a technique, based upon surface photometry analysis, to compute robustly and accurately the moments of a shape in an image, and use them as inputs for the estimation algorithm. As a consequences, an ellipse-based camera calibration is introduced, which uses the relationships between the specification of a 3D-ellipse, the moments of its image and the calibration parameters . These equations are partially extended to models including distortions .En vision par ordinateur, il est souvent utile de connaître un modèle de la caméra pour pouvoir obtenir des informations 3D à partir des images. Nous présentons une méthode de calibration (ou calibrage) de caméra conçue pour fournir une estimation précise des paramètres du modèle de prise de vue. Pour avoir une bonne estimation, il est nécessaire avant tout d'avoir de bonnes mesures dans l'image. Nous avons choisi d'utiliser les moments géométriques d'une région comme les données 'image' à fournir à l'algorithme, car ils peuvent être calculés avec précision et robustesse en se fondant sur la photométrie des surfaces. Cela nous a conduits à développer une calibration à base d'ellipses. Pour cela, le lien exact entre la description d'une ellipse de l'espace 3D et les moments d'ordre inférieur ou égal à deux de sa projection a dû être explicité en fonction des paramètres de la calibration. Ces relations sont en partie étendues au cas où les distorsions sont modélisées

Calibration de camera fondée sur les ellipses

Projet SYNTIMWe present an ellipse-based camera calibration. Correct measures in the image are required to perform the camera model estimation. We suggest a technique, based upon surface photometry, allowing to compute robustly and accurately the moments of a shape in an image, and use them as inputs for the estimation algorithm. Connections between the specification of a 3D-ellipse, the moments of its image and calibration parameters are described. These equations are partially extended to models including distortions. Then, the parameters estimation is a non linear problem solved by an iterative algorithm. Tests with synthetic and real images are described and discussed for different camera models.Une méthode de calibration de caméra à base d'ellipses est présentée. Pour avoir une bonne estimation des paramètres du modèle, il est nécessaire d'avoir de bonnes mesures dans l'image. Les moments géométriques d'une région ont été choisis comme les données à fournir à l'algorithme d'estimation, car ils peuvent être calculés, dans une image, avec précision et robustesse en se fondant sur la photométrie des surfaces. Le lien exact, entre la description d'une ellipse de l'espace 3D et les moments d'ordre inférieur ou égal à deux de sa projection, est explicité en fonction des paramètres de la calibration. Ces relations sont en partie étendues au cas où les distorsions sont modélisées. Alors, l'estimation des paramètres est un problème non linéaire qui est résolu avec un algorithme itératif. Des résultats sur des images réelles et synthétiques sont présentés et discutés pour différents types de modèles de la caméra

Dowe really need an accurate calibration pattern?

The metrology of calibration patterns is often a real problem in computer vision to obtain a reliable estimation of the intrinsic and extrinsic parameters that model a video camera device . In order to take into account these errors a self-calibration method is described, that enables us to compute in the same time the traditional calibration parameters and the 3D geometry of the calibration pattern using a multi-images calibration algorithm . Experimental results shows that the proposed algorithm leads to reliable calibration results and proves that calibration errors no longer depend on the accuracy of calibration point measurement, but on the accuracy of calibration point detection in the image plane .Cet article soulève le problème de l'influence des erreurs introduites par la métrologie d'une mire d'étalonnage sur la détermination des paramètres intrinsèques d'un capteur vidéo. Afin de s'affranchir de ces erreurs, une approche d'autocalibrage est décrite permettant conjointement d'estimer les paramètres internes du capteur vidéo et la géométrie de la mire, au sein d'un formalisme d'étalonnage multi-images. Par la problématique qu'il soulève, cet article cotoie les approches de Shape from Motion et d'Auto-calibrage des capteurs, en gardant cependant la spécificité d'être décrit selon un formalisme photogrammétrique et donc d'intégrer implicitement les aberrations géométriques des objectifs. Nous nous sommes attachés à insister sur l'aspect descriptif de la méthode pour permettre aux lecteurs une vision globale de la mise en oeuvre du procédé