• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.1-15
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• 2000

To reconstruct 3- D shape, It is a common strategy to acquire multiple range Images from different viewpoints and integrate them into a common coordinates In this paper, we particularly focus on the registration and integration processes for combining all range Images into one surface model. For the registration, we propose the 2-step registration algorithm, which consists of 2 steps the rough registration step using all data points and the fine registration step using the high-curved data points For the integration, we propose a new algorithm, referred to as ‘multi-registration’ technique, to alleviate the error accumulation problem, which occurs during applying the pair-wise registration to each range image sequentially, in order to transform them into a common reference frame Intensive experiments are performed on the various real range data In experiments, all range images were registered within 1 minutes on Pentium 150MHz PC The results show that the proposed algorithms registrate and integrate multiple range Images within a tolerable error bound in a reasonable computation time, and the total error between all range Images are equalized with our proposed algorithms.

• Proceedings of the KSRS Conference
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• v.1
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• pp.500-503
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• 2006

To adjust the discrepancy between Light Detection and Ranging (LIDAR) strips, previous researches generally have been conducted using conjugate features, which are called feature-based approaches. However, irrespective of the type of features used, the adjustment process relies upon the existence of suitable conjugate features within the overlapping area and the ability of employed methods to detect and extract the features. These limitations make the process complex and sometimes limit the applicability of developed methodologies because of a lack of suitable features in overlapping areas. To address these drawbacks, this paper presents a methodology using area-based algorithms. This approach is based on the scheme that discrepancies make complex the local height variations of LIDAR data whithin overlapping area. This scheme can be helpful to determine an appropriate transformation for adjustment in the way that minimizes the geographical complexity. During the process, the contour tree (CT) was used to represent the geological characteristics of LIDAR points in overlapping area and the Iterative Closest Points (ICP) algorithm was applied to automatically determine parameters of transformation. After transformation, discrepancies were measured again and the results were evaluated statistically. This research provides a robust methodology without restrictions involved in methods that employ conjugate features. Our method also makes the overall adjustment process generally applicable and automated.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.108-114
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• 2015

Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.296-305
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• 2016

This paper proposes a framework to automatically align Dental range image captured by depth sensors like the Microsoft Kinect. Aligning dental images by intraoral scanning technology is a difficult problem for applications requiring accurate model of dental-scan datasets with efficiency in computation time. The most important thing in dental scanning system is accuracy of the dental prosthesis. Previous approaches in intraoral scanning uses a Z-buffer ICP algorithm for fast registration, but it is relatively not accurate and it may cause cumulative errors. This paper proposes additional Alignment using the rough result comes after intraoral scanning alignment. It requires that Each Depth Image of the total set shares some overlap with at least one other Depth image. This research implements the automatically additional alignment system that aligns all depth images into Completed model by computing a network of pairwise registrations. The order of the each individual transformation is derived from a global network and AABB box overlap detection methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.91-102
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• 2017

Backpack-mounted mapping system is firstly introduced for flexible movement in indoor spaces where satellite-based localization is not available. With the achieved advances in miniaturization and weight reduction, use of LiDAR (Light Detection and Ranging) sensors in mobile platforms has been increasing, and indeed, they have provided high-precision information on indoor environments and their surroundings. Previous research on the development of backpack-mounted mapping systems, has concentrated mostly on the improvement of data processing methods or algorithms, whereas practical system components have been determined empirically. Thus, in the present study, a simulator for a LiDAR sensor (Velodyne VLP-16), was developed for comparison of the effects of diverse conditions on the backpack system and its operation. The simulated data was analyzed by visual inspection and comparison of the data sets' statistics, which differed according to the LiDAR arrangement and moving speed. Also, the data was used as input to a point-cloud registration algorithm, ICP (Iterative Closest Point), to validate its applicability as pre-analysis data. In fact, the results indicated centimeter-level accuracy, thus demonstrating the potentials of simulation data to be utilized as a tool for performance comparison of pointdata processing methods.

• Journal of Mechanical Science and Technology
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• v.19 no.12
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• pp.2213-2223
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• 2005

In order to reconstruct a full 3D human model in reverse engineering (RE), a 3D scanner needs to be placed arbitrarily around the target model to capture all part of the scanned surface. Then, acquired multiple scans must be registered and merged since each scanned data set taken from different position is just given in its own local co-ordinate system. The goal of the registration is to create a single model by aligning all individual scans. It usually consists of two sub-steps: rough and fine registration. The fine registration process can only be performed after an initial position is approximated through the rough registration. Hence an automated rough registration process is crucial to realize a completely automatic RE system. In this paper an automated rough registration method for aligning multiple scans of complex human face is presented. The proposed method automatically aligns the meshes of different scans with the information of features that are extracted from the estimated principal curvatures of triangular meshes of the human face. Then the roughly aligned scanned data sets are further precisely enhanced with a fine registration step with the recently popular Iterative Closest Point (ICP) algorithm. Some typical examples are presented and discussed to validate the proposed system.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.208-210
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• 2003

RED(Random Early Detection) 라우터를 성공적으로 배치하기 위해서는 RED 알고리즘을 구성하는 각 파라미터를 적절히 조절할 수 있어야 한다. 특히 다수의 TCP 연결이 하나의 라우터를 공유하는 네트워크 병목구간에서는 그 중요성이 한층 강조된다. 그러나 RED가 TD 라우터와 같은 네트워크 퍼포먼스를 유지하면서 ICP 커넥션 간 페어니스(fairness)를 향상시키기 위해서는, 네트워크 상황에 따라 다수의 컨트롤 파라미터 값을 적절하게 설정해줘야만 한다. 문제는 다양한 네트워크 환경에서 효과적으로 RED 알고리즘이 동작하기 위해 파라미터를 설정하는 것이 매우 어렵다는 것이다. 본 논문에서는 네트워크 상황에 따라 동적으로 RED 파라미터를 조절하면서 빠르게 안정적인 상태로 적응하는 진보된 RED 알고리즘인 ea-RED(Efficient Adaptive RED)를 디자인하고 구현하여 알고리즘의 효율성을 확인한다.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.1
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• pp.57-65
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• 2004

Introduction : The phantom that includes high density materials such as steel was custom-made to fix lung and bone in order to evaluation inhomogeneity correction at the time of conducting radiation therapy to treat lung cancer. Using this, values resulting from the inhomogeneous correction algorithm are compared on the 2 and 3 dimensional radiation therapy planning systems. Moreover, change in dose calculation was evaluated according to inhomogeneous by comparing with the actual measurement. Materials and Methods : As for the image acquisition, inhomogeneous correction phantom(Pig's vertebra, steel(8.21g/cm3), cork(0.23 g/cm3)) that was custom-made and the CT(Volume zoom, Siemens, Germany) were used. As for the radiation therapy planning system, Marks Plan(2D) and XiO(CMS, USA, 3D) were used. To compare with the measurement value, linear accelerator(CL/1800, Varian, USA) and ion chamber were used. Image, obtained from the CT was used to obtain point dose and dose distribution from the region of interest (ROI) while on the radiation therapy planning device. After measurement was conducted under the same conditions, value on the treatment planning device and measured value were subjected to comparison and analysis. And difference between the resulting for the evaluation on the use (or non-use) of inhomogeneity correction algorithm, and diverse inhomogeneity correction algorithm that is included in the radiation therapy planning device was compared as well. Results : As result of comparing the results of measurement value on the region of interest within the inhomogeneity correction phantom and the value that resulted from the homogeneous and inhomogeneous correction, gained from the therapy planning device, margin of error of the measurement value and inhomogeneous correction value at the location 1 of the lung showed $0.8\%$ on 2D and $0.5\%$ on 3D. Margin of error of the measurement value and inhomogeneous correction value at the location 1 of the steel showed $12\%$ on 2D and $5\%$ on 3D, however, it is possible to see that the value that is not correction and the margin of error of the measurement value stand at $16\%$ and $14\%$, respectively. Moreover, values of the 3D showed lower margin of error compared to 2D. Conclusion : Revision according to the density of tissue must be executed during radiation therapy planning. To ensure a more accurate planning, use of 3D planning system is recommended more so than the 2D Planning system to ensure a more accurate revision on the therapy plan. Moreover, 3D Planning system needs to select and use the most accurate and appropriate inhomogeneous correction algorithm through actual measurement. In addition, comparison and analysis through TLD or film dosimetry are needed.

• Conservation Science in Museum
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• v.22
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• pp.15-26
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• 2019

This study was focused on the three-dimensional convergence modeling that can multilaterally analyze internal and external shapes of the Sam-Chongtong Hand Canon by optical precision scanning optimized for acquiring the surface shape and X-ray CT scanning used for obtaining the internal shape. First, the scanning results were converted by compatible extension, after which three-dimensional deviation analysis was conducted to verify mutual conformities. Accordingly, most (56.98%) deviations between the two scanning models was found be ±0.1mm. This result did not influence registration and merging based on the ICP algorithm. The merged data exhibited the external surface color, detailed shapes, internal width, and structure of the hand canon. The three-dimensional model based on optical surface scanning and X-ray CT scanning can be used for traditional technique interpretation as well as digital documentation of cultural heritage. In the future, it will contribute to deliver accessible scientific information of exhibits for visitors.