• The Korean Journal of Applied Statistics
• /
• v.18 no.1
• /
• pp.83-98
• /
• 2005

Exploring distributional patterns of multivariate data is very essential in understanding the characteristics of given data set, as well as in building plausible models for the data. For that purpose, low-dimensional visualization methods have been developed by many researchers along various directions. As one of methods, Kohonen's SOM (Self-Organizing Map) is prominent. SOM compresses the volume of the data, yields abstraction from the data and offers visual display on low-dimensional grids. Although it is proven quite effective, it has one undesirable property: SOM's display is discrete. In this study, we propose two techniques for enhancing quality of SOM's display, so that SOM's display becomes continuous. The proposed methods are demonstrated in two numerical examples.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.6
• /
• pp.625-635
• /
• 2014

Multiple strips are required for large area mapping using ALS (Airborne Laser Scanner) system. LiDAR (Light Detection And Ranging) data collected from the ALS system has discrepancies between strips due to systematic errors of on-board laser scanner and GPS/INS, inaccurate processing of the system calibration as well as boresight misalignments. Such discrepancies deteriorate the overall geometric quality of the end products such as DEM (Digital Elevation Model), building models, and digital maps. Therefore, strip adjustment for minimizing discrepancies between overlapping strips is one of the most essential tasks to create seamless point cloud data. This study implemented area-based matching (ABM) to determine conjugate features for computing 3D transformation parameters. ABM is a well-known method and easily implemented for this purpose. It is obvious that the exact same LiDAR points do not exist in the overlapping strips. Therefore, the term "conjugate point" means that the location of occurring maximum similarity within the overlapping strips. Coordinates of the conjugate locations were determined with sub-pixel accuracy. The major drawbacks of the ABM are sensitive to scale change and rotation. However, there is almost no scale change and the rotation angles are quite small between adjacent strips to apply AMB. Experimental results from this study using both simulated and real datasets demonstrate validity of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7C
• /
• pp.544-553
• /
• 2012

A vehicle localization technology is an essential component to support many smart-vehicle applications, e.g. collision warning, adaptive cruise control, and so on. In this paper, we present a new vehicle localization algorithm based on the fusion of the sensing estimates from the local sensors and the GPS estimates from the inter-vehicle communications. The proposed algorithm consists of the greedy location data mapping algorithm and the position refinement algorithm. The former maps a sensing estimate with a GPS estimate based on the distance between themselves, and then the latter refines the GPS estimate of the subject vehicle based on the law of large numbers. From the numerical results, we demonstrate that the accuracy of the proposed algorithm outperforms that of the existing GPS estimates by at least 30 % in the longitudinal direction and by at least 60% in the lateral direction.

• Journal of information and communication convergence engineering
• /
• v.9 no.1
• /
• pp.83-88
• /
• 2011

Abstract. Image segmentation is always a challenging task in computer vision as well as in pattern recognition. Nowadays, this method has great importance in the field of stereo vision. The disparity information extracting from the binocular image pairs has essential relevance in the fields like Stereoscopic (3D) Imaging Systems, Virtual Reality and 3D Graphics. The term 'disparity' represents the horizontal shift between left camera image and right camera image. Till now, many methods are proposed to visualize or estimate the disparity. In this paper, we present a new technique to visualize the horizontal disparity between two stereo images based on image segmentation method. The process of comparing left camera image with right camera image is popularly known as 'Stereo-Matching'. This method is used in the field of stereo vision for many years and it has large contribution in generating depth and disparity maps. Correlation based stereo-matching are used most of the times to visualize the disparity. Although, for few stereo image pairs it is easy to estimate the horizontal disparity but in case of some other stereo images it becomes quite difficult to distinguish the disparity. Therefore, in order to visualize the horizontal disparity between any stereo image pairs in more robust way, a novel stereo-matching algorithm is proposed which is named as "Quadtree Segmentation of Pixels Disparity Estimation (QSPDE)".

• The KIPS Transactions:PartB
• /
• v.15B no.6
• /
• pp.553-560
• /
• 2008

The amount of image data used in medical institution is increasing rapidly with great development of medical technology. Therefore, an automation method that use image processing description, rather than manual macrography of doctors, is required for the analysis large medical data. Specially, medical image registration, which is the process of finding the spatial transform that maps points from one image to the corresponding points in another image, and 3D analysis and visualization skills for a series of 2D images are essential technologies. However, a high establishment cost raise a budget problem, and hence small scaled hospitals hesitate importing these medical visualizing system. In this paper, we propose a visualization system which allows user to manage datasets and manipulates medical images registration using an open source graphics tool - VTK(Visualization Tool Kit). The propose of our research is to get more accurate 3D diagnosis system in less expensive price, compared to existing systems.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.4
• /
• pp.246-254
• /
• 2020

In this paper, we propose a learning based compressive sensing algorithm for the purpose of side scan sonar image denoising. The proposed method is based on Iterative Shrinkage and Thresholding Algorithm (ISTA) framework and incorporates a powerful strategy that reinforces the non-linearity of deep learning network for improved performance. The proposed method consists of three essential modules. The first module consists of a non-linear transform for input and initialization while the second module contains the ISTA block that maps the input features to sparse space and performs inverse transform. The third module is to transform from non-linear feature space to pixel space. Superiority in noise removal and memory efficiency of the proposed method is verified through various experiments.

• Journal of Microbiology and Biotechnology
• /
• v.9 no.5
• /
• pp.631-636
• /
• 1999

The thermostable endo-chitosanase gene from the isolated strain Bacillus sp. KFB-C108 was identified on the basis of a phylogenetic analysis of the 16S rRNA gene sequence, and was cloned into plasmid pUCl8 using E. coli $DH5\alpha$ as the host strain. Positive clones carrying recombinant plasmids (pKCHO I and pKCHO II) containing chitosanase activity were selected using the direct activity staining method. Detailed physical maps showed the two plasmid inserts were identical except that the KCHO II insert (2.6 kb) was 1.8 kb smaller than that of the KCHO I. The recombinant plasmids were analyzed to determine the essential region for chitosanase activity, and a 1.3-kb fragment (KCHO-6) was subcloned into pTrc99A using the EcoRI and BamHI sites to construct pTrc99A/KCHO-6(pTrEB13). The resulting plasmid exerted high chitosanase activity upon transformation of E. coli $DH5{\alpha}cells$, overproducing about 20 times more in the cloned cells than in the wild-type cells. The cloned chitosanase protein exhibited the same molecular weight and catalytic activity similar to those of Bacillus sp. KFB-C108. The cloned enzyme was an endo-type that produced a chitosan tetramer as the major reaction product; however, it produced no monomers or dimers.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.2
• /
• pp.97-106
• /
• 2006

Site index is an essential tool to estimate forest productivity. Generally, a site index equation is developed and used from the relationship between stand age and dominant tree heights. However, there is a limit to the use of the site index equation in the application of variable ages, environmental influence, and estimation of site index for the unstocked forest. Therefore, it has been attempted to develop a new site index equation based on various environmental factors including site, climate, and topographical variables. This study was conducted to develop a site index equation based on the relationship between site index and environmental factors for the species of Pinus koraiensis in Yangpyung-Gun, Gyunggi Province. The influence of climatic factors (temperature and solar irradiation ratio), topographical factors (elevation, slope, ratio of slope to valley and aspect) and soil profiles (soil depth by layer and soil consistency) on site index were evaluated by multiple regression analysis. Five environmental factors were selected in the final site index equation for Pinus koraiensis. The site index equation developed in this study was also verified by three evaluation statistics: model's estimation bias, model's precision, and mean square error of measurement. Based on the site index equation, the number of productive areas for Pinus koraiensis were estimated by applying GIS technique to digitized forest maps. In addition, the distribution of productive areas was compared with the areas of current distribution of Pinus koraiensis. It is expected that the results obtained in this study could provide valuable information about the amount and distribution of productive areas for Pinus koraiensis reforestation.

• Korean Journal of Remote Sensing
• /
• v.15 no.1
• /
• pp.31-38
• /
• 1999

In this paper, we introduce an algorithm for the ortho-rectification of high resolution pushbroom-type satellite images. The generation of ortho-images in the ultimate level of the satellite image preprocessing which also includes systematic geocoding and precision geocoding. It is also essential for the mapping of satellite images because topotraphic maps are based on the orthographic projection. The newly developed ortho-image generation algorithm introduced in this paper is on the line of the algorithms previously developed (Shin and Lee, 1997; Shin e 1998). Various experimental results are shown in this paper. The results show that the algorithm completely eliminates the disparities in the perspectively viewed images which were caused by the terrain height. The absolute accuracy of the developed algorithm depends on the accuracy of the camera model and the digital elevation model used.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1163-1175
• /
• 2021

In autonomous driving, road markings are an essential element for object tracking, path planning and they are able to provide important information for localization. This paper presents an approach to update and measure road surface markers with HD maps as well as matching using inverse perspective mapping. The IPM removes perspective effects from the vehicle's front camera image and remaps them to the 2D domain to create a bird-view region to fit with HD map regions. In addition, letters and arrows such as stop lines, crosswalks, dotted lines, and straight lines are recognized and compared to objects on the HD map to determine whether they are updated. The localization of a newly installed object can be obtained by referring to the measurement value of the surrounding object on the HD map. Therefore, we are able to obtain high accuracy update results with very low computational costs and low-cost cameras and GNSS/INS sensors alone.