• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.373-380
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• 2022

This paper considers a method of fast correspondence matching for iterative closest point (ICP) algorithm. In robotics, the ICP algorithm and its variants have been widely used for pose estimation by finding the translation and rotation that best align two point clouds. In computational perspectives, the main difficulty is to find the correspondence point on the reference point cloud to each observed point. Jump-table-based correspondence matching is one of the methods for reducing computation time. This paper proposes a method that corrects errors in an existing jump-table-based correspondence matching algorithm. The criterion activating the use of jump-table is modified so that the correspondence matching can be applied to the situations, such as point-cloud registration problems with highly curved surfaces, for which the existing correspondence-matching method is non-applicable. For demonstration, both hardware and simulation experiments are performed. In a hardware experiment using Hokuyo-10LX LiDAR sensor, our new algorithm shows 100% correspondence matching accuracy and 88% decrease in computation time. Using the F1TENTH simulator, the proposed algorithm is tested for an autonomous driving scenario with 2D range-bearing point cloud data and also shows 100% correspondence matching accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.242-249
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• 2011

In this paper, the correspondence matching method of stereo images was proposed by means of sampling projective transformation matrix in planar region of scene. Though this study is based on RANSAC, it does not use uniform distribution by random sampling in RANSAC, but use multi non-uniform computed from difference in positions of feature point of image or templates matching. The existing matching method sampled that the correspondence is presumed to correct by use of the condition which the correct correspondence is almost satisfying, and applied RANSAC by matching the correspondence into one to one, but by sampling in stages in multi probability distribution computed for image in the proposed method, the correct correspondence of high probability can be sampled among multi correspondence candidates effectively. In the result, we could obtain many correct correspondence and verify effectiveness of the proposed method in the simulation and experiment of real images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.44-53
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• 1992

In this paper, a matching method is proposed to improve the correct matching rate in stereo correspondence matching in which the fingerprint of zero-crossing points on the scale-space is used as the robust matching feature. The dynamic programming, which is appropriate for the fingerprint feature, is introduced for correspondence matching. We also improve the matching rate by using the post-processing for correcting mismatched points. In simulation, we apply the proposed algorithm to the synthetic and real images and obtain good matching results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.116-123
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• 1990

Most algorithms utilized the horizontal epipolar lines for solving the correspondence problem in 3-D computer vision. However, the requirement is very difficult to be satisfied in real situations. In this paper, we propose a binocular-stereo matching algorithm, based on line matching method, which does not require the horizontal epipolar lines of the extreme pixels of a given line segment and two circles whose radius is equal to the maximum disparity. And we use the features including the direction of line segments, edge strength and cross-correlation for line matching. The experimental results show that the proposed algorithm can be a useful tool for solving the correspondence problem in 3-D computer vision.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.177-181
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• 2001

본 논문에서는 칼라차 영상을 이용하여 물체들의 움직임을 분석하고 이동 형태들의 대한 RGB 특징 값을 추출하였으며 그 동안 미해결 과제로 남았던 이동 물체들 사이의 영역정합(matching)과 군집화 (clustering)를 이용하여 대응(Correspondence)관계를 확인하는 문제를 해결하여 이동 물체들을 추구하여 보았다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1523-1533
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• 1997

Image registration is concerned with the establishment of correspondence between images of the same scene with translational, rotational, and scaling differences. The estimated transformation parameters between images are very important information in the field of many applications. In this paper, we propose a shape matching scheme for finding correspondence points for images with various differences, Tranditional solutions to this area are unreliable for the rotational and schaling changes between images, and the feature extraction of partially occluded scene. To solve those problems, dominant points on digital curves are detected by scale-space filtering, and initial matching is performed by similarity measure of cumulative curvatures for dominant points. For initial matching segments pairs, optimal matching points are calculated using dynamic programming.Finally, transformation parameters are estimated.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.1
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• pp.151-163
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• 1990

In this paper, rule-based stereo algorithm is explored to obtain three dimensional information of an object. In the preprocessing of the stereo matching, feature points of stereo images must be less sensitive to noise and well linked. For this purpose, a new feature points detection algorithm is developed. For performing the stereo matching which is most important process of the stereo algorithm, the feature representation of feature points is first described. The feature representation is then used for a rule-based stereo algorithm to determine the correspondence between the input stereo images. Finally, the three dimensional information of the object is determined from the correspondence of the feature points of right and left images.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.26-32
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• 2011

This paper proposes a new method to process panoramic image stitching using SURF(Speeded Up Robust Features). Panoramic image stitching is considered a problem of the correspondence matching. In computer vision, it is difficult to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. However, SURF algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform). In this work, we also describe an efficient approach to decreasing computation time through the homography estimation using RANSAC(random sample consensus). RANSAC is a robust estimation procedure that uses a minimal set of randomly sampled correspondences to estimate image transformation parameters. Experimental results show that our method is robust to rotation, zoom, Gaussian noise and illumination change of the input images and computation time is greatly reduced.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.58-67
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• 2009

A correspondence matching is one of the important tasks in computer vision, and it is not easy to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. A SURF(Speeded Up Robust Features) algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform) with closely maintaining the matching performance. However, because SURF considers only gray image and local geometric information, it is difficult to match corresponding points on the image where similar local patterns are scattered. In order to solve this problem, this paper proposes an extended SURF algorithm that uses the invariant color and global geometric information. The proposed algorithm can improves the matching performance since the color information and global geometric information is used to discriminate similar patterns. In this paper, the superiority of the proposed algorithm is proved by experiments that it is compared with conventional methods on the image where an illumination and a view point are changed and similar patterns exist.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.