• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.66-69
• /
• 2002

This article outlines the capabilities of a viewer component called GridViewer, and proves its reusability. GridViewer was designed for the construction of the image display part of GIS or remote sensing application software, and consequently it is particularly straightforward to closely couple GridViewer with access to very large images. Displaying is performed through pyramid structure, which enables to treat very large dataset up to several gigabytes in size under the limited capability of PC. GridViewer is free from responsibility to handle various formats of raster data files by taking grid coverage, which is designed by OGC to promote interoperability between implementations done by data vendors and software vendors providing analysis and grid processing implementations. GridViewer differs from other such viewer by allowing for clients to extend its function and capability by using small set of methods originally implemented in it. We show its reusability and expandability by applying it in developing application programs performing various functions not supported originally by the GridViewer COM component.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2012.08a
• /
• pp.184-184
• /
• 2012

Recently, InGaN/GaN multi-quantum well grown on GaN pyramid structures have attracted much attention due to their hybrid characteristics of quantum well, quantum wire, and quantum dot. This gives us broad band emission which will be useful for phosphor-free white light emitting diode. On the other hand, by using quantum dot emission on top of the pyramid, site selective single photon source could be realized. However, these structures still have several limitations for the single photon source. For instance, the quantum efficiency of quantum dot emission should be improved further. As detection systems have limited numerical aperture, collection efficiency is also important issue. It has been known that micro-cavities can be utilized to modify the radiative decay rate and to control the radiation pattern of quantum dot. Researchers have also been interested in nano-cavities using localized surface plasmon. Although the plasmonic cavities have small quality factor due to high loss of metal, it could have small mode volume because plasmonic wavelength is much smaller than the wavelength in the dielectric cavities. In this work, we used localized surface plasmon to improve efficiency of InGaN qunatum dot as a single photon emitter. We could easily get the localized surface plasmon mode after deposit the metal thin film because lnGaN/GaN multi quantum well has the pyramidal geometry. With numerical simulation (i.e., Finite Difference Time Domain method), we observed highly enhanced decay rate and modified radiation pattern. To confirm these localized surface plasmon effect experimentally, we deposited metal thin films on InGaN/GaN pyramid structures using e-beam deposition. Then, photoluminescence and time-resolved photoluminescence were carried out to measure the improvement of radiative decay rate (Purcell factor). By carrying out cathodoluminescence (CL) experiments, spatial-resolved CL images could also be obtained. As we mentioned before, collection efficiency is also important issue to make an efficient single photon emitter. To confirm the radiation pattern of quantum dot, Fourier optics system was used to capture the angular property of emission. We believe that highly focused localized surface plasmon around site-selective InGaN quantum dot could be a feasible single photon emitter.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.3
• /
• pp.213-224
• /
• 1992

An encoding technique based on region splitting and vector quantization is proposed for the lower level Laplacian pyramid images. The lower level Laplacian pyramid images have lower variance than higher levels but a great influence on compression ration due to large spatial area. And so from data compression viewpoint, we subdivide them with variance thresholding into two regions such as one called : flat region” and the other “edge region”, and encode the flat region with its mean value and the edge region as vector quantization method. The edge region can be reproduced faithfully and significant improvement on compression ratio can be accomplished with a little degradation of PSNR in spite of the effect of large flat region since the codebook used is generated from the edge region only on from the entire image including the flat region. It can be verified by computer simulation results that proposed method is more efficient in compression ratio and processing time than the conventional encoding technique of vector quantization.

• Journal of Korean Society for Geospatial Information Science
• /
• v.20 no.3
• /
• pp.41-48
• /
• 2012

Using multi-sensor or multi-temporal high resolution satellite images together is essential for efficient applications in remote sensing area. The purpose of this paper is to estimate geometric difference of translations between high-resolution optical and SAR images automatically. The geometric and radiometric pre-processing steps were fulfilled to calculate the similarity between optical and SAR images by using Mutual Information method. The coarsest-level pyramid images of each sensor constructed by gaussian pyramid method were generated to estimate the initial translation difference of the x, y directions for calculation efficiency. The precise geometric difference of translations was able to be estimated by applying this method from coarsest-level pyramid image to original image in order. Yet even when considered only translation between optical and SAR images, the proposed method showed RMSE lower than 5m in all study sites.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.6
• /
• pp.1624-1635
• /
• 1996

Palletized color images are the dominant type of the image used on Internet and World-Wide Web. In spite of this, most image compression and progressive transmission algorithm have been designed for continuous-tone images. Pallettize images. Palletized images differ from continuous-tone images in such a aspect that values are lookup table indices a new pyramid structure for compression and progressive transmission of a palletized image. In the proposed pyramid structure, the color of a node at higher level is the one that occupies the most part in 4 sons and each node is represented by a type code and several color codes. Since the proposed method do not exploit spatial correlation in an image, it is ideally applied to lossless compression and progressive transmission of palletized images. We have confirmed this through the experimental results.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.153-166
• /
• 2022

Identifying fine cracks in steel bridge facilities is a challenging task of structural health monitoring (SHM). This study proposed an end-to-end crack image segmentation framework based on a one-step Convolutional Neural Network (CNN) for pixel-level object recognition with high accuracy. To particularly address the challenges arising from small object detection in complex background, efforts were made in loss function selection aiming at sample imbalance and module modification in order to improve the generalization ability on complicated images. Specifically, loss functions were compared among alternatives including the Binary Cross Entropy (BCE), Focal, Tversky and Dice loss, with the last three specialized for biased sample distribution. Structural modifications with dilated convolution, Spatial Pyramid Pooling (SPP) and Feature Pyramid Network (FPN) were also performed to form a new backbone termed CrackDet. Models of various loss functions and feature extraction modules were trained on crack images and tested on full-scale images collected on steel box girders. The CNN model incorporated the classic U-Net as its backbone, and Dice loss as its loss function achieved the highest mean Intersection-over-Union (mIoU) of 0.7571 on full-scale pictures. In contrast, the best performance on cropped crack images was achieved by integrating CrackDet with Dice loss at a mIoU of 0.7670.

• Spatial Information Research
• /
• v.16 no.2
• /
• pp.193-206
• /
• 2008

If stereo images is used for Digital Elevation Model (DEM) generation, a DEM is generally made by matching left image against right image from stereo images. In stereo matching, tie-points are used as initial match candidate points. The number and distribution of tie-points influence the matching result. DEM made from matching result has errors such as holes, peaks, etc. These errors are usually interpolated by neighbored pixel values. In this paper, we propose the DEM generation method combined with automatic tie-points extraction using existing DEM, image pyramid, and interpolating new DEM using existing DEM for more reliable DEM. For test, we used IKONOS, QuickBird, SPOT5 stereo images and a DTED level 2 data. The test results show that the proposed method automatically makes reliable DEMs. For DEM validation, we compared heights of DEM by proposed method with height of existing DTED level 2 data. In comparison result, RMSE was under than 15 m.

• The Journal of the Korea Contents Association
• /
• v.18 no.11
• /
• pp.447-454
• /
• 2018

This paper proposes a depth image generation algorithm of stereo images using a deep learning model composed of a CNN (convolutional neural network). The proposed algorithm consists of a feature extraction unit which extracts the main features of each parallax image and a depth learning unit which learns the parallax information using extracted features. First, the feature extraction unit extracts a feature map for each parallax image through the Xception module and the ASPP(Atrous spatial pyramid pooling) module, which are composed of 2D CNN layers. Then, the feature map for each parallax is accumulated in 3D form according to the time difference and the depth image is estimated after passing through the depth learning unit for learning the depth estimation weight through 3D CNN. The proposed algorithm estimates the depth of object region more accurately than other algorithms.

• Journal of Educational Research in Mathematics
• /
• v.9 no.1
• /
• pp.121-132
• /
• 1999

We have compared Korean and American mathematics curriculums in 5 areas: whole number(concepts and its operations); geometry; pattern and relations; measurements; statistics and probability. We have found significant differences in geometry area. Korean curriculums contain simple planar figures (circles, triangles, rectangles, and squres) and some of the spatial figures until 3rd grades. But in America they learn various planar and spatial fugures(cone, pyramid, triangular prism, etc) since the 1st grade starts. They also start the 1st grade by dealing with topological concepts like open/closed, inside/outside, order, etc. As the grade goes on, students learn other geometrical concepts like congruence, symmetry, 3-dimensional views. We also found that American curriculum focuses on students' activities and courages communication through projects, groupwork, journal writing, etc. It's also superior in respects of motivation, and connections with real life and other subjects. Korean curriculum needs more improvements in these aspects. Furthermore for lower graders reviewing sections need to be enhanced for feedback.

• Korean Institute of Interior Design Journal
• /
• v.19 no.6
• /
• pp.112-120
• /
• 2010

Human can recognize the environment by detecting spatial perception, and most of environmental perception depends on visual perception. In view that the acquisition of spatial information is accomplished through visual recognition, analysis of visual structure contained in the space is thought to be very important sector in studying the characteristic of the space. The history of studies on visual structure of space, however, wasn't too long, and furthermore most of the theories up to now focused on static and planar principles. Under this circumstance, this study is intended to suggest new theory by combining Isovist theory and VGA theory that have been actively discussed as the theory on visual perception-based spatial structure and supplementing them between each other to expand into 3-dimensional model. The suggested theory is a complex principle in dimensional and dynamic form in consideration of visual direction, which forms 3-dimentional virtual model that enables visualization of the property of spatial structure as the routine discriminating whether visual connection is made between viewing point and target point, and the target point is included in the visual field quadrangular pyramid or not. Such model was built up by an analysis application where four probe paths were applied to simulate the visual structure that occurs in virtual space, and then the characteristics were analyzed through quantification. In result, in spite of the path with equal space and equal length, significant difference in the acquired quantity of spatial information could be found depending on the probe sequence. On the contrary, it was found that probe direction may not affect the acquired quantity of information and visual property of the space.