• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1080-1087
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• 2005

Significant computations for full search (FS) motion estimation have been a big obstacle in real-time video coding and recent MPEG-4 AVC (advanced video coding) standard requires much more computations than conventional MPEG-2 for motion estimation. To reduce an amount of computation of full search (FS) algorithm for fast motion estimation, we propose a new and fast matching algorithm without any degradation of predicted images like the conventional FS. The computational reduction without any degradation in predicted image comes from fast elimination of impossible candidate motion vectors. We obtain faster elimination of inappropriate motion vectors using efficient matching units from localization of complex area in image data and dithering order based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination (PDE) algorithm, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.505-510
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• 2016

This paper presents a searching method of corresponding points robust to rotational error for scan-matching used for SLAM(Simultaneous Localization and Mapping) in mobile robot. A differential driving mechanism is one of the most popular type for mobile robot. For driving curved path, this type controls the velocities of each two wheels independently. This case increases a wheel slip of the mobile robot more than the case of straight path driving. And this is the reason of a drifting problem. To handle this problem and improves the performance of scan-matching, this paper proposes a searching method of corresponding points using extraction of a closest point based on rotational radius of the mobile robot. To verify the proposed method, the experiment was conducted using LRF(Laser Range Finder). Then the proposed method is compared with an existing method, which is an existing method based on euclidian closest point. The result of our study reflects that the proposed method can improve the performance of searching corresponding points.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.3
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• pp.299-304
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• 2021

Purpose. The purpose of the present study was to investigate the effects of image matching experience of operators on the accuracy and working time of image registration between radiographic and optical scan images. Materials and methods. Computed tomography and optical scan of a dentate dental arch were obtained. Image matching between the computed tomography and the optical scan (IDC S1, Amann Girrbach, Koblah, Austria) was performed using the point-based automatic registration method in planning software programs (Implant Studio, 3Shape, Copenhagen, Denmark) using two different experience conditions on image registration: experienced group and inexperienced group (n = 15 per group, N = 30). The accuracy of image registration in each group was evaluated by measuring linear discrepancies between matched images, and working time was recorded. Independent t test was used to statistically analyze the result data (α = .05). Results. In the linear deviation, no statistically significant difference was found between the experienced and inexperienced groups. Meanwhile, the working time for image registration was significantly shorter in the experienced group than in the inexperienced group (P = .007). Conclusion. Difference in the image matching experience may not influence the accuracy of image registration of optical scan to computed tomography when the point-based automatic registration was used, but affect the working time for the image registration.

• Journal of Korean Dental Science
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• v.13 no.1
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• pp.28-34
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• 2020

Purpose: The purpose of this study was to investigate the influence of different implant computer software on the accuracy of image registration between radiographic and optical scan data. Materials and Methods: Cone-beam computed tomography and optical scan data of a partially edentulous jaw were collected and transferred to three different computer softwares: Blue Sky Plan (Blue Sky Bio), Implant Studio (3M Shape), and Geomagic DesignX (3D systems). In each software, the two image sets were aligned using a point-based automatic image registration algorithm. Image matching error was evaluated by measuring the linear discrepancies between the two images at the anterior and posterior area in the direction of the x-, y-, and z-axes. Kruskal-Wallis test and a post hoc Mann-Whitney U-test with Bonferroni correction were used for statistical analyses. The significance level was set at 0.05. Result: Overall discrepancy values ranged from 0.08 to 0.30 ㎛. The image registration accuracy among the software was significantly different in the x- and z-axes (P=0.009 and <0.001, respectively), but not different in the y-axis (P=0.064). Conclusion: The image registration accuracy performed by a point-based automatic image matching could be different depending on the computer software used.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.281-287
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• 2010

This study compares transformation algorithms for co-registration of terrestrial laser scan data. Pair-wise transformation which is used for transformation of scan data from more than two different view accumulates errors. ICP algorithm commonly used for co-registration between scan data needs initial geometry information. And it is difficult to co-register simultaneously because of too many control points when managing scan at the same time. Therefore, this study perform global registration technique using matching points. Matching points are extracted automatically from intensity image by SIFT and global registration is performed using GP analysis. There are advantages for operation speed, accuracy, automation in suggested global registration algorithm. Through the result from it, registration algorithms can be developed by considering accuracy and speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.165-175
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• 2005

If the interlaced scan type camera moves while an image is filming from the camera, blur is often created from the misalignment of the two images of even and odd lines. This paper proposed an algorithm which removes the misalignment of the even and odd line images cased by the vibration of the interlaced scan type camera. The blurred original image is separated into the even and the odd line images as half size. Based on these two images, two full sized images are generated using interpolation technique. If a big difference between these two interpolated images is generated, the original image is taken while the camera is moving. In this case, a deblurred image is obtained with the alignment of these separated two images through feature point extraction, feature point matching, sub-pixel matching, outlier detection, and image mosaicking processes. This paper demonstrated that the proposed algorithm can create clear images from blurred images caused by various camera motions.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.385-394
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• 2017

Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).

• 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 Korean Society for Precision Engineering
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• v.14 no.11
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• pp.102-109
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• 1997

A two-degree-of freedom (TDF) $H_{\infty}$controller for a seeker scan loop is presented for the purpose of improving scanning performances. The perturbed plant model is characterized via the normalized coprime factorization. The TDF $H_{\infty}$controller is designed based on the loop shaping design procedure and model matching approach, and its performances are evaluated and compared with those of a previous work. It is demonstrated that the proposed TDF $H_{\infty}$controller is more effective to the control of the seeker scan loop than the previous controller.oller.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.745-752
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• 2016

We suggest an efficient Simultaneous Localization and 3D Polygon Map Building (SLAM) method with Kinect depth sensor for mobile robots in indoor environments. In this method, Kinect depth data is separated into row planes so that scan line segments are on each row plane. After grouping all scan line segments from all row planes into line groups, a set of 3D Scan polygons are fitted from each line group. A map matching algorithm then figures out pairs of scan polygons and existing map polygons in 3D, and localization is performed to record correct pose of the mobile robot. For 3D map-building, each 3D map polygon is created or updated by merging each matched 3D scan polygon, which considers scan and map edges efficiently. The validity of the proposed 3D SLAM algorithm is revealed via experiments.