• Journal of Computational Design and Engineering
• /
• v.1 no.3
• /
• pp.202-212
• /
• 2014

To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components' accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components' accuracy by comparing each component's point cloud data scanned by laser scanners and the ship's design data formatted in CAD cannot be processed efficiently when (1) extract components from point cloud data include irregular obstacles endogenously, or when (2) registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles' shadows. The ICP (Iterative Closest Point) algorithm conducts a registration of the two sets of data after the proper registration's direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.4
• /
• pp.345-352
• /
• 2020

To preserve and restore tidal flats and prevent safety accidents, it is necessary to construct tidal flat topographic information including the exact location and shape of tidal creeks. In the tidal flats where the field surveying is difficult to apply, airborne LiDAR surveying can provide accurate terrain data for a wide area. On the other hand, we can economically obtain relatively high-resolution data from UAV (Unmanned Aerial Vehicle) surveying. In this study, we proposed the methodology to generate high-resolution topographic information of tidal flats effectively by integrating airborne LiDAR and UAV point clouds. For the purpose, automatic ICP (Iterative Closest Points) registration between two different datasets was conducted and tidal creeks were extracted by applying CSF (Cloth Simulation Filtering) algorithm. Then, we integrated high-density UAV data for tidal creeks and airborne LiDAR data for flat grounds. DEM (Digital Elevation Model) and tidal flat area and depth were generated from the integrated data to construct high-resolution topographic information for large-scale tidal flat map creation. As a result, UAV data was registered without GCP (Ground Control Point), and integrated data including detailed topographic information of tidal creeks with a relatively small data size was generated.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.8
• /
• pp.597-602
• /
• 2016

In image guided surgery, a patient registration process is a critical process for the successful operation, which is required to use pre-operative images such as CT and MRI during operation. Though several patient registration methods have been studied, we concentrate on one method that utilizes 3D surface measurement data in this paper. First, a hand-held 3D surface measurement device measures the surface of the patient, and secondly this data is matched with CT or MRI data using optimization algorithms. However, generally used ICP algorithm is very slow without a proper initial location and also suffers from local minimum problem. Usually, this problem is solved by manually providing the proper initial location before performing ICP. But, it has a disadvantage that an experience user has to perform the method and also takes a long time. In this paper, we propose a method that can accurately find the proper initial location automatically. The proposed method finds the proper initial location for ICP by converting 3D data to 2D curvature images and performing image matching. Curvature features are robust to the rotation, translation, and even some deformation. Also, the proposed method is faster than traditional methods because it performs 2D image matching instead of 3D point cloud matching.

• Journal of Information Processing Systems
• /
• v.16 no.1
• /
• pp.120-131
• /
• 2020

In order to solve the problem of point clouds coordinate conversion of non-directional scanners, this paper proposes a basic Rodrigues rotation method. Specifically, we convert the 6 degree-of-freedom (6-DOF) rotation and translation matrix into the uniaxial rotation matrix, and establish the equation of objective vector conversion based on the basic Rodrigues rotation scheme. We demonstrate the applicability of the new method by using a bar-shaped emboss point clouds as experimental input, the three-axis error and three-term error as validate indicators. The results suggest that the new method does not need linearization and is suitable for optional rotation angle. Meanwhile, the new method achieves the seamless splicing of point clouds. Furthermore, the coordinate conversion scheme proposed in this paper performs superiority by comparing with the iterative closest point (ICP) conversion method. Therefore, the basic Rodrigues rotation method is not only regarded as a suitable tool to achieve the conversion of point clouds, but also provides certain reference and guidance for similar projects.

• Journal of Biomedical Engineering Research
• /
• v.30 no.1
• /
• pp.34-40
• /
• 2009

Transforms including translation and rotation are required for registering two or more images. In medical applications, different registration methods have been applied depending on the structures: for rigid bodies such as bone structures, affine transformation was widely used. In most previous research, a single transform was used for registering the whole images, which resulted in low registration accuracy especially when the degree of deformation was high between two images. In this paper, a novel registration method is introduced which is based image sub-division and bilinear interpolation of transformations. The proposed method enhanced the registration accuracy by 40% comparing with Trimmed ICP for registering color and MRI images.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.4
• /
• pp.659-665
• /
• 2016

In this paper, we propose a novel position accuracy enhancement method of a low-end GPS using digital map information. The latest digital map has various kinds of information on geographical features. The proposed method uses position information of lane marks among the geographical features. We define the position information of lane marks as the reference points. The position information of a low-end GPS acquired for a period of time is defined as the source points. In the proposed method, rotation and translation matrices between the reference and the source points are calculated by using an Iterative Closest Point(ICP) algorithm. The source points are transformed by the obtained rotation and translation matrices. Finally, the transformed source points are projected on the reference points. Through these processes, the position accuracy of a low-end GPS is ultimately enhanced. To verify the proposed method, the various real experimental results are presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.5
• /
• pp.459-467
• /
• 2014

The importance of fusion and association using established spatial information has increased gradually with the production and supply of various spatial data by public institutions. The generation of necessary spatial information without field investigation and additional surveying can reduce time, labor, and financial costs. However, the study of the integration of the newly introduced road name address map with the digital map is very insufficient. Even though the use of the road name address map is encouraged for public works related to spatial information, the digital map is still widely used because it is the national basic map. Therefore, in this study, building matching and update were performed to associate the digital map with the road name address map. After geometric calibration using the block-based ICP (Iterative Closest Point) method, multi-scale corresponding pair searching with hierarchical clustering was applied to detect the multi-type match. The accuracy assessment showed that the proposed method is more than 95% accurate and the matched building layer of the two maps is useful for the integrated application and fusion. In addition, the use of the road name address map, which carries the latest and most frequently renewed data, enables cost-effective updating of new buildings.

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

• Spatial Information Research
• /
• v.19 no.2
• /
• pp.37-46
• /
• 2011

Recently in the field of GIS(Geographic Information System), data integration from various sources has become an important topic in order to use spatial data effectively. In general, the integration of spatial data is accomplished by navigating corresponding space object and combining the information interacting with each object. But it is very difficult to navigate an object which has correspondence with one in another dataset. Many matching methods have been studied for navigating spatial object. The purpose of this paper is development of method for searching correspondent spatial object considering local position error which is remained even after coordinate transform ation when two different building data sets integrated. To achieve this goal, we performed coordinate transformation and overlapped two data sets and generated blocks which have similar position error. We matched building objects within each block using similarity and ICP algorithm. Finally, we tested this method in the aspect of applicability.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.19 no.5
• /
• pp.552-560
• /
• 2013

In this paper, an optimization algorithm for the block assembly accuracy control assessment is proposed with consideration for the current block assembly process and accuracy control procedure used in the shipbuilding site. The objective function of the proposed algorithm consists of root mean square error of the distances between design and measured data of the other control points with respect to a specific point of the whole control points. The control points are divided into two groups: points on the control line and the other points. The grouped data are used as criteria for determining the combination of 6 degrees of freedom in the registration process when constituting constraints and calculating objective function. The optimization algorithm is developed by using combination of the sampling method and the point to point relation based modified ICP algorithm which has an allowable error check procedure that makes sure that error between design and measured point is under allowable error. According to the results from the application of the proposed algorithm with the design and measured data of two blocks data which are verified and validated by an expert in the shipbuilding site, it implies that the choice of whole control points as target points for the accuracy calculation shows better results than that of the control points on the control line as target points for the accuracy of the calculation and the best optimized result can be acquired from the accuracy calculation with a fixed point on the control line as the reference point of the registration.