A recursive approach to space resection using straight lines

An approach using straight lines as features to solve the photogrammetric space resection problem is presented. An explicit mathematical model relating straight lines, in both object and image space, is used. Based on this model, Kalman Filtering is applied to solve the space resection problem. The recursive property of the filter is used in an iterative process which uses the sequentially estimated camera location parameters to feedback to the feature extraction process in the image. This feedback process leads to a gradual reduction of the image space for feature searching, and consequently eliminates the bottleneck due to the high computational cost of the image segmentation phase. It also enables feature extraction and the determination of feature correspondence in image and object space in an automatic way, i.e., without operator interference. Results obtained from simulated and real data show that highly accurate space resection parameters are obtained as well as a progressive processing time reduction. The obtained accuracy, the automatic correspondence process, and the short related processing time show that the proposed approach can be used in many real-time machine vision systems, making possible the implementation of applications not feasible until now.

Classificação automática de padrões projetados por um sistema de luz estruturada

One of the main problems in Computer Vision and Close Range Digital Photogrammetry is 3D reconstruction. 3D reconstruction with structured light is one of the existing techniques and which still has several problems, one of them the identification or classification of the projected targets. Approaching this problem is the goal of this paper. An area based method called template matching was used for target classification. This method performs detection of area similarity by correlation, which measures the similarity between the reference and search windows, using a suitable correlation function. In this paper the modified cross covariance function was used, which presented the best results. A strategy was developed for adaptative resampling of the patterns, which solved the problem of deformation of the targets due to object surface inclination. Experiments with simulated and real data were performed in order to assess the efficiency of the proposed methodology for target detection. The results showed that the proposed classification strategy works properly, identifying 98% of targets in plane surfaces and 93% in oblique surfaces.

A photogrammetric method for single image orientation and measurement

The aim of this paper is to present a photogrammetric method for determining the dimensions of flat surfaces, such as billboards, based on a single digital image. A mathematical model was adapted to generate linear equations for vertical and horizontal lines in the object space. These lines are identified and measured in the image and the rotation matrix is computed using an indirect method. The distance between the camera and the surface is measured using a lasermeter, providing the coordinates of the camera perspective center. Eccentricity of the lasermeter center related to the camera perspective center is modeled by three translations, which are computed using a calibration procedure. Some experiments were performed to test the proposed method and the achieved results are within a relative error of about 1 percent in areas and distances in the object space. This accuracy fulfills the requirements of the intended applications. © 2005 American Society for Photogrammetry and Remote Sensing.

Extração de feições rodoviárias em imagens digitais: Metodologias desenvolvidas pelo GP-F&VC

Several kinds of research in road extraction have been carried out in the last 6 years by the Photogrammetry and Computer Vision Research Group (GPF&VC - Grupo de Pesquisa em Fotogrametria e Visão Computacional). Several semi-automatic road extraction methodologies have been developed, including sequential and optimizatin techniques. The GP-F&VC has also been developing fully automatic methodologies for road extraction. This paper presents an overview of the GP-F&VC research in road extraction from digital images, along with examples of results obtained by the developed methodologies.

Automatic extraction of road seeds from high-resolution aerial images

This article presents an automatic methodology for extraction of road seeds from high-resolution aerial images. The method is based on a set of four road objects and another set of connection rules among road objects. Each road object is a local representation of an approximately straight road fragment and its construction is based on a combination of polygons describing all relevant image edges, according to some rules embodying road knowledge. Each one of the road seeds is composed by a sequence of connected road objects, in which each sequence of this type can be geometrically structured as a chain of contiguous quadrilaterals. Experiments carried out with high-resolution aerial images showed that the proposed methodology is very promising in extracting road seeds. This article presents the fundamentals of the method and the experimental results, as well.

Técnica autorradiográfica para investigação geológica - Estudo de caso na área do projeto rio preto

The auto-radiography is a photographic method to registrate in sensitive emulsion the spatial distribution a rays emitted by radioisotopes of a sample or an object. The auto-radiography was applied to detect the presence of radioactive minerals in some samples of schists and gneisses from the Ticunzal Formation, Northeast Goiás State, aiming to implement the use of this technique in LABIDRO - Hydrochemistry and Isotopes Laboratory of the Department of Petrology and Metallogenesis, State University of São Paulo/Campus of Rio Claro.

Extração semi-automática de rodovias em um par de imagens aéreas digitais utilizando geometria epipolar e programação dinâmica

The purpose of this paper is to introduce a methodology for semi-automatic road extraction from aerial digital image pairs by using dynamic programming and epipolar geometry. The method uses both images from where each road feature pair is extracted. The operator identifies the corresponding road featuresand s/he selects sparse seed points along them. After all road pairs have been extracted, epipolar geometry is applied to determine the automatic point-to-point correspondence between each correspondent feature. Finally, each correspondent road pair is georeferenced by photogrammetric intersection. Experiments were made with rural aerial images. The results led to the conclusion that the methodology is robust and efficient, even in the presence of shadows of trees and buildings or other irregularities.

Um estudo sobre o osu do modelo de cor RGB no proceso de correspondência por correlação

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aligning the CMS muon chambers with the muon alignment system during an extended cosmic ray run

The alignment system for the muon spectrometer of the CMS detector comprises three independent subsystems of optical and analog position sensors. It aligns muon chambers with respect to each other and to the central silicon tracker. System commissioning at full magnetic field began in 2008 during an extended cosmic ray run. The system succeeded in tracking muon detector movements of up to 18 mm and rotations of several milliradians under magnetic forces. Depending on coordinate and subsystem, the system achieved chamber alignment precisions of 140-350 μm and 30-200 μrad, close to the precision requirements of the experiment. Systematic errors on absolute positions are estimated to be 340-590 μm based on comparisons with independent photogrammetry measurements. © 2010 IOP Publishing Ltd and SISSA.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

The influence of subpixel measurement on digital camera calibration

The aim of this work is to evaluate the influence of point measurements in images, with subpixel accuracy, and its contribution in the calibration of digital cameras. Also, the effect of subpixel measurements in 3D coordinates of check points in the object space will be evaluated. With this purpose, an algorithm that allows subpixel accuracy was implemented for semi-automatic determination of points of interest, based on Fõrstner operator. Experiments were accomplished with a block of images acquired with the multispectral camera DuncanTech MS3100-CIR. The influence of subpixel measurements in the adjustment by Least Square Method (LSM) was evaluated by the comparison of estimated standard deviation of parameters in both situations, with manual measurement (pixel accuracy) and with subpixel estimation. Additionally, the influence of subpixel measurements in the 3D reconstruction was also analyzed. Based on the obtained results, i.e., on the quantification of the standard deviation reduction in the Inner Orientation Parameters (IOP) and also in the relative error of the 3D reconstruction, it was shown that measurements with subpixel accuracy are relevant for some tasks in Photogrammetry, mainly for those in which the metric quality is of great relevance, as Camera Calibration.

Generating virtual images from oblique frames

Image acquisition systems based on multi-head arrangement of digital camerasare attractive alternatives enabling a larger imaging area when compared to a single framecamera. The calibration of this kind of system can be performed in several steps or byusing simultaneous bundle adjustment with relative orientation stability constraints. Thepaper will address the details of the steps of the proposed approach for system calibration,image rectification, registration and fusion. Experiments with terrestrial and aerial imagesacquired with two Fuji FinePix S3Pro cameras were performed. The experiments focusedon the assessment of the results of self-calibrating bundle adjustment with and withoutrelative orientation constraints and the effects to the registration and fusion when generatingvirtual images. The experiments have shown that the images can be accurately rectified andregistered with the proposed approach, achieving residuals smaller than one pixel. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Photogrammetric refinement of laser-based building roof contours

In this paper a photogrammetric method is proposed for refining 3D building roof contours extracted from airborne laser scanning data. It is assumed that laser-derived planar faces of roofs are potentially accurate, while laser-derived building roof contours are not well defined. First, polygons representing building roof contours are extracted from a high-resolution aerial image. In the sequence, straight-line segments delimitating each building roof polygon are projected onto the corresponding laser-derived roof planes by using a new line-based photogrammetric model. Finally, refined 3D building roof contours are reconstructed by connecting every pair of photogrammetrically- projected adjacent straight lines. The obtained results showed that the proposed approach worked properly, meaning that the integration of image data and laser scanning data allows better results to be obtained, when compared to the results generated by using only laser scanning data. © 2013 IEEE.