• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• ETRI Journal
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• v.34 no.1
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• pp.87-97
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• 2012

This study presents an automatic matching method for generating a dense, accurate, and discontinuity-preserved digital surface model (DSM) using multiple images acquired by an aerial digital frame camera. The proposed method consists of two main procedures: area-based multi-image matching (AMIM) and stereo-pair epipolar line matching (SELM). AMIM evaluates the sum of the normalized cross correlation of corresponding image points from multiple images to determine the optimal height of an object point. A novel method is introduced for determining the search height range and incremental height, which are necessary for the vertical line locus used in the AMIM. This procedure also includes the means to select the best reference and target images for each strip so that multi-image matching can resolve the common problem over occlusion areas. The SELM extracts densely positioned distinct points along epipolar lines from the multiple images and generates a discontinuity-preserved DSM using geometric and radiometric constraints. The matched points derived by the AMIM are used as anchor points between overlapped images to find conjugate distinct points using epipolar geometry. The performance of the proposed method was evaluated for several different test areas, including urban areas.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.907-917
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• 2019

Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.6
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• pp.611-620
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• 1989

In this paper, Fingerprint matching method which is able to confirm one's identity using microcomputer is discussed. In matching method, fingerprint image is thinned and we extracted feature point data which is composed of position and direction of end-point and branch-point. Identification is conducted by decision of disagreement between reference finger print and input fingerprint us ing this extracted data. After averaging and binariztion process, thining method is conducted. Restoration process is carried out to seek precise feature pointdatd. We compensate position difference of reference fingerprint and input fingerprint, which is divied end-point and branch-point, and translated and rotated its position. Using this compensdate difference of position, we decide whether fingerp-print identity is true or not.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.11
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• pp.879-885
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• 1990

An intergral equation is derived for surface current distribution of cylinders with end cap using quasistatic approximation method. The moment method is applied for numerical solution. Point matching method using Cubic B-spline function as a basis function, delta function as a weighting function is applied for moment method. And also, the influencial relation in accordance with structural variation is analized in case of spheroidal end up cap type and flat type.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.901-904
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• 2000

A direct authentication from gray-scale image, instead of the conventional multi-step preprocessing, is proposed using Gabor filter-based features from the gray-scale fingerprint around core point. The core point is located as a reference point for the translation invariant matching. And its principal symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then fingerprint is divided into non-overlapping blocks with respect to the core point and features are directly extracted form the blocked gray level fingerprint using Gabor filter. The proposed fingerprint authentication is based on the Euclidean distance between the corresponding Gabor features of the input and the template fingerprints. Experiments are conducted on 300${\times}$300 fingerprints obtained from a CMOS sensor with 500 dpi resolution, and the proposed method could lower the False Reject Rate(FRR) to 18.2% under False Acceptance Rate(FAR) of 0%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.

• Journal of KIISE
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• v.43 no.5
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• pp.562-568
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• 2016

Point cloud data can be expressed in a specific coordinate system of a data set with a large number of points, to represent any form that generally has different characteristics in the three-dimensional coordinate space. This paper is aimed at finding a cylindrical pipe in the point cloud of the three-dimensional coordinate system using RANSAC, which is faster than the conventional Hough Transform method. In this study, the proposed cylindrical pipe is estimated by combining the results of parameters based on two mathematical models. The two kinds of mathematical models include a sphere and line, searching the sphere center point and radius in the cylinder, and detecting the cylinder with straightening of center. This method can match cylindrical pipe with relative accuracy; furthermore, the process is rapid except for normal estimation and segmentation. Quick cylinders matching could benefit from laser scanning and reverse engineering construction sectors that require pipe real-time estimates.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.446-449
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• 2000

A direct RTI(Rotation and translation invariant) fingerprint identification is proposed using the GCMs(generalized complex moments) and Gabor filter-based features from the grey level fingerprint around core point. The core point is located as reference point for the translation invariant matching. And its symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then, fingerprint is divided into non-overlapping blocks with respect to the core point and, in contrast to minutiae-based method using various processing steps, features are directly extracted from the blocked grey level fingerprint using Gabor filter, which provides information contained in a particular orientation in the image. The Proposed fingerprint identification is based on the Euclidean distance of the corresponding Gabor features between the input and the template fingerprint. Experiments are conducted on 300 ${\times}$ 300 fingerprints obtained from the CMOS sensor with 500 dpi resolution, and the proposed method could obtain 97% identification rate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.461-469
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• 2001

Existing area-based stereo algorithms rely heavily on rectangular windows for computing correspondence. While the algorithms with the rectangular windows are efficient, they generate relatively large matching errors due to variations of disparity profiles near depth discontinuities and doesnt take into account local deformations of the windows due to projective distortion. In this paper, in order to deal with these problems, a new correlation function with 4 directional line masks, based on robust estimator, is proposed for the selection of potential matching points. These points is selected to consider depth discontinuities and reduce effects on outliers. The proposed matching method finds an arbitrarily-shaped variable window around a pixel in the 3d array which is constructed with the selected matching points. In addition, the method take into account the local deformation of the variable window with a constant disparity, and perform the estimation of sub-pixel disparities. Experiments with various synthetic images show that the proposed technique significantly reduces matching errors both in the vicinity of depth discontinuities and in continuously smooth areas, and also does not be affected drastically due to outlier and noise.