• Journal of information and communication convergence engineering
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• v.7 no.1
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• pp.1-6
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• 2009

In order to obtain a 3-D urban model, an abstraction of the surface model is required. This paper describes works on the 3D reconstruction and modeling by the grouping 3D line segments extracted from the stereo matching of edges, which is derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.78-82
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• 2007

This paper propose a building reconstruction method of urban area for a 3D GIS with stereo images. The 3D reconstruction is performed by the grouping 3D line segments extracted from the stereo matching of salient edges which are derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

• ETRI Journal
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• v.35 no.5
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• pp.939-942
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• 2013

We provide a new solution for the projective reconstruction problem based on coupled line cameras (CLCs) and their geometric properties. The proposed solution is composed of a series of optimized steps, and each step is more efficient than those of the initial solution proposed in [1]. We also give a new determinant condition for rectangle determination, which leads to less ambiguity in implementation. The key steps of the proposed solution can be represented with more compact analytic equations due to the intuitive geometric interpretations of the projective reconstruction problem based on CLCs: the center of projection corresponds to the intersection point of the two solution circles of each line camera involved.

• Korean Journal of Computational Design and Engineering
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• v.20 no.4
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• pp.357-366
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• 2015

We review recent research results on coupled line cameras (CLC) as a new geometric tool to reconstruct a scene quadrilateral from image quadrilaterals. Coupled line cameras were first developed as a camera calibration tool based on geometric insight on the perspective projection of a scene rectangle to an image plane. Since CLC comprehensively describes the relevant projective structure in a single image with a set of simple algebraic equations, it is also useful as a geometric reconstruction tool, which is an important topic in 3D computer vision. In this paper we first introduce fundamentals of CLC with reals examples. Then, we cover the related works to optimize the initial solution, to extend for the general quadrilaterals, and to apply for cuboidal reconstruction.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.59-64
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• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.1-10
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• 2022

Single-view reconstruction (SVR) is a fundamental method in computer vision. Often used for reconstructing human-made environments, the Manhattan world assumption presumes that planes in the real world exist in mutually orthogonal directions. Accordingly, this paper addresses an automatic SVR algorithm for Manhattan worlds. A method for estimating the directions of planes using graph-cut optimization is proposed. After segmenting an image from extracted line segments, the data cost function and smoothness cost function for graph-cut optimization are defined by considering the directions of the line segments and neighborhood segments. Furthermore, segments with the same depths are grouped during a depth-estimation step using a minimum spanning tree algorithm with the proposed weights. Experimental results demonstrate that, unlike previous methods, the proposed method can identify complex Manhattan structures of indoor and outdoor scenes and provide the exact boundaries and intersections of planes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.69-74
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• 2004

In this paper, we propose a novel method for improving defect-detection performance based on reconstruction of line-scan camera images using both the projection profiles and color space transform. The proposed method consists of RGB region segmentation, representative value reconstruction using the tracing system, and Y image reconstruction using color-space transformation. Through experiments it is demonstrated that the performance using the reconstructed image is better than that using aerial image for LCD surface inspection.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.244-247
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• 1995

A technique is presented for evaluating spinal deformity of a human back by extracting a spinal line based on 3-D topograpic reconstruction of the back from its moire image. A given moire image is differentiatedby DOG filter to extract moire stripes. The stripes are then assigned labels and the labels are interpolated by the Lagrange polynomial to yield the undulation of the back which gives a relative 3-D shape of the back. A valley is searched on the undulation near the middle part of the back and the valley line is finally extracted as an approximated spinal line. The mean differenceand the variance between the spinal line and the middle line are calculated and reported. Experiment is performed employing real moire images ofjunior-high school students' backs and some of the results are shown with discussion.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.293-299
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• 2012

Electrical impedance tomography is an imaging modality for determining the electrical properties inside a domain. Small currents are injected and the resulting voltages are measured through the electrodes. The internal electrical properties are reconstructed based on these voltage and current data. In this paper, a novel on-line Landweber algorithm was developed to fast estimate the resistivity distribution in the inverse calculation. Additionally, to enhance the reconstruction performance, a step-length was computed from the eigenvalue of the weighting matrix. The numerical experiments have been performed to evaluate the reconstruction performance of the proposed method.

• Journal of IKEEE
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• v.12 no.1
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• pp.51-58
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• 2008

This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract the useful building location information from the generated disparity map to obtain the segmentation of interested objects and thus reduce significantly unnecessary line segment extracted in low level feature extraction step. Hypothesis selection is carried out by using undirected graph in which close cycles represent complete rooftops hypotheses, and hypothesis are finally tested to contruct building model. We test the proposed method with synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the buildings can be efficiently used for the task of building detection and reconstruction from aerial images.