• Proceedings of the KSRS Conference
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• v.1
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• pp.98-101
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• 2006

In general, stereo images are widely used to remote sensing or photogrametric applications for the purpose of image understanding and feature extraction or cognition. However, the most cases of these stereo-based application deal with 2-D satellite images or the airborne photos so that its main targets are generation of small-scaled or large-scaled DEM(Digital Elevation Model) or DSM(Digital Surface Model), in the 2.5-D. Contrast to these previous approaches, the scope of this study is to investigate 3-D stereo processing and visualization of true geo-referenced 3-D features based on anaglyph technique, and the aim is at the prototype development for stereo visualization system of complex typed 3-D GIS features. As for complex typed 3-D features, the various kinds of urban landscape components are taken into account with their geometric characteristics and attributes. The main functions in this prototype are composed of 3-D feature authoring and modeling along with database schema, stereo matching, and volumetric visualization. Using these functions, several technical aspects for migration into actual 3-D GIS application are provided with experiment results. It is concluded that this result will contribute to more specialized and realistic applications by linking 3-D graphics with geo-spatial information.

• Journal of Sensor Science and Technology
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• v.25 no.5
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• pp.310-319
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• 2016

Three types of gap sensors, a capacitive gap sensor, an eddy current gap sensor, and a Hall effect gap sensor are described and evaluated through experiments for the purpose of precise gap sensing for micrometer scale movement, and a novel type of differential hall effect gap sensor is proposed. Each gap sensor is analyzed in terms of resolution and environment dependency including temperature dependency. Furthermore, a transport system for AMOLED deposition is introduced as a typical application of gap sensors, which are recently receiving considerable attention. Based on the analyses, the proposed differential Hall effect gap sensor is found to be the most suitable gap sensor for precise gap sensing, especially for application to a transport system for AMOLED deposition. The sensor shows resolution of $0.63mV/{\mu}m$ for the overall range of the gap from 0 mm to 2.5 mm, temperature dependency of $3{\mu}m/^{\circ}C$ from $20^{\circ}C$ to $30^{\circ}C$, and a monotonic characteristic for the gap between the sensor and the target.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.188-192
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• 2012

In this study, a carbon nanotube (CNT) flexible strain sensor was fabricated with CNT based epoxy and rubber composites for tactile sensing. The flexible strain sensor can be fabricated as a long fibrous sensor and it also may be able to measure large deformation and contact information on a structure. The long and flexible sensor can be considered to be a continuous sensor like a dendrite of a neuron in the human body and we named the sensor as a biomimetic artificial neuron. For the application of the neuron in biomimetic engineering, an ANMS (Artificial Neuron Matrix System) was developed by means of the array of the neurons with a signal processing system. Moreover, a strain positioning algorithm was also developed to find localized tactile information of the ANMS with Labview for the application of an artificial e-skin.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.517-529
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• 2009

Many satellite image fusion techniques have been developed in order to produce a high resolution multispectral (MS) image by combining a high resolution panchromatic (PAN) image and a low resolution MS image. Heretofore, most high resolution image fusion techniques have used IKONOS and QuickBird images. Recently, GeoEye-1, offering the highest resolution of any commercial imaging system, was launched. In this study, we have experimented with GeoEye-1 images in order to evaluate which fusion algorithms are suitable for these images. This paper presents compares and evaluates the efficiency of five image fusion techniques, the $\grave{a}$ trous algorithm based additive wavelet transformation (AWT) fusion techniques, the Principal Component analysis (PCA) fusion technique, Gram-Schmidt (GS) spectral sharpening, Pansharp, and the Smoothing Filter based Intensity Modulation (SFIM) fusion technique, for the fusion of a GeoEye-1 image. The results of the experiment show that the AWT fusion techniques maintain more spatial detail of the PAN image and spectral information of the MS image than other image fusion techniques. Also, the Pansharp technique maintains information of the original PAN and MS images as well as the AWT fusion technique.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.63-71
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• 2012

Most of sensor networks are difficult to be debugged, verified, and upgraded once they are deployed in the fields, for they are usually deployed in real world and large scale. Therefore, before deploying the sensor networks, we should test and verify them sufficiently in realistic testbeds. However, since we need to control physical environments which interact with sensor networks, it takes much of time and cost to test and verify sensor networks at the level of resource-constrained sensor nodes in such environments. This paper proposes an efficient software framework for evaluating and verifying sensor networks in the view points of network and application operations (i.e., accuracy of sensing algorithms). Applying the proposed software framework to the development of a simulator for a smart parking application based on wireless sensor network, this paper verifies the feasibility of the proposed framework.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.271-285
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• 2009

Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.379-383
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• 2006

Satellite imagery may contain large regions covered with atmospheric aerosol. A highresolution satellite imagery affected by non-homogenous aerosol cover should be processed for land cover study and perform the radiometric calibration that will allow its future application for Korea Multi-Purpose Satellite (KOMPSAT) data. In this study, aerosol signal was separated from high resolution satellite data based on the reflectance separation method. Since aerosol removal has a good sensitivity over bright surface such as man-made targets, aerosol optical thickness (AOT) retrieval algorithm could be used. AOT retrieval using Look-up table (LUT) approach for utilizing the transformed image to radiometrically compensate visible band imagery is processed and tested in the correction of satellite scenery. Moderate Resolution Imaging Spectroradiometer (MODIS), EO-l/HYPERION data have been used for aerosol correction and AOT retrieval with different spatial resolution. Results show that an application of the aerosol detection for HYPERION data yields successive aerosol separation from imagery and AOT maps are consistent with MODIS AOT map.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.13-24
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• 2014

Satellite remote sensing data have been valuable tool for volcanic ash monitoring. In this study, we present the results of application of satellite remote sensing data for monitoring of volcanic ash for three major volcanic eruption cases (2008 Chait$\acute{e}$n, 2010 Eyjafjallaj$\ddot{o}$kull, and 2011 Shinmoedake volcanoes). Volcanic ash detection products based on the Moderate Resolution Imaging Spectro-radiometer (MODIS) observation data using infrared brightness temperature difference technique were compared to the forward air mass trajectory analysis by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. There was good correlation between MODIS volcanic ash image and trajectory lines after the volcanic eruptions, which support the feasibility of using the integration of satellite observed and model derived data for volcanic ash forecasting.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.185-191
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• 2007

Remote sensing images are multispectral image data collected from several band divided by wavelength ranges. The classification of remote sensing images is the method of classifying what has similar spectral characteristics together among each pixel composing an image as the important algorithm in this field. This paper presents a pattern classification method of remote sensing images by applying a possibilistic fuzzy c-means (PFCM) algorithm. The PFCM algorithm is a hybridization of a FCM algorithm, which adopts membership degree depending on the distance between data and the center of a certain cluster, combined with a PCM algorithm, which considers class typicality of the pattern sets. In this proposed method, we select the training data for each class and perform supervised classification using the PFCM algorithm with spectral signatures of the training data. The application of the PFCM algorithm is tested and verified by using Landsat TM and IKONOS remote sensing satellite images. As a result, the overall accuracy showed a better results than the FCM, PCM algorithm or conventional maximum likelihood classification(MLC) algorithm.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.222-227
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• 2002

This research will examine into the capabilities of KOMPSAI-1 EOC image application in the field of urban environment and at the same time, with that as its foundation, come to understand the urban changes of the study areas. This research is constructed in three stages: Firstly, for application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, change detection method is applied fur the systematic monitoring of land use changes, which utilizes multi-temporal EOC images. Lastly, by using the results of the application of land use changes, the existing land use map is updated. Consequently, the land-use change patterns are monitored, which utilize multi-temporal panchromatic EOC image data; and application potentials of ancillary data fur updating existing data can be presented. In this research, with the use of the land use change, monitoring of urban growth has been carried out, and the potential for the application of KOMPSAT-1 EOC images and the scope of application was examined. Henceforth, the future expansion of the scope of application of KOMPSAT-1 EOC image is anticipated.