• Proceedings of the KIEE Conference
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• 2007.11a
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• pp.154-155
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• 2007

This paper describes frequency response of two-mass system for gyroscope applications. The two-mass system of the proposed device is adapted to the sensing part of the gyroscope in this research. Two-mass system has two resonant peaks and wide flat region between two resonant peaks. The resonant frequency of driving part is in this flat region. Therefore, frequency tuning is not necessary for mode matching. In the proposed device, resonant frequency is designed as 7183 Hz in driving part. Mass ratio of two masses in sensing part is 0.1 and device size is 6 mm $\times$ 6 mm. The device is fabricated by SiOG process. The fabricated spring width is increased from $4{\mu}m$ to $4.5{\sim}4.7{\mu}m$, and the measured resonant frequency is 8392 Hz in driving mode. We operated the sensing part using parallel plate of proof mass to verify the sensing part. It is confirmed the device has a wide fiat region in frequency response curve and the resonant frequency of the driving part is in the wide flat region of sensing mode.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1039-1041
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• 2003

Ocean color products derived from remote sensing satellite data are useful for monitoring the sea water quality such as the concentrations of chlorophyll, sediments and dissolved organic matter. Currently, ocean color products derived from MODIS data can be requested from NASA over the internet. However, due to the bandwidth limitation of most users in this region, and the time delay in data delivery, the products cannot be use for near-real time monitoring of sea water chlorophyll. CRISP operates a MODIS data receiving station for environmental monitoring purposes. MODIS data have been routinely received and processed to level 1B. We have adapted the higher level processing algorithms from the Institutional Algorithms provided by NASA to run in a standalone environment. The implemented algorithms include the MODIS ocean color algorithms. Seasonal chlorophyll concentration composite can be compiled for the region. By comparing the near-real time chlorophyll product with the seasonal composite, anomaly in chlorophyll concentration can be detected.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.223-231
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• 2003

With the negative influences and damage from Asian dust increasing, it's getting important to investigate the climate and soil condition of the source region of Asian dust. There is a high possibility that the desertification and the drastic decrease of plants in China and Mongolia make worse the situation (bad effects of Asian Dust). To detect the movement of Asian dust caused by air circulation, we need to watch the state of the source region to get useful information for the prevention of the dust pollution, and to predict what part of China will become the source region. Therefore, using TOMS aerosol index data, NCEP reanalysis data that is Remote Sensing data from 1981 to 2000 (except 1993~1996, 4 years), for 16 years, examined the relation between the dust occurrence and weather elements. Dust occurrence appeared much in spring season from March to May in study areas. It had a dry climate during that season as follows : relative humidity about 20~40%, temperature about -5~5$^{\circ}C$, precipitation about 33-180 mm, wind speed about 4-10 ms-1. Dust occurrence and weather element annual change in study areas decreased gradually till 1990, but in Gobi desert the incidence of dust occurrence increased since 1997. As a result, found out that the more the precipitation, the less dust occurrence, because the precipitation and surface wind speed had a direct influence on the soil of the source region of dust.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.611-622
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• 2012

This study proposed two multisensor fusion methods for segment-based image classification utilizing a region-growing segmentation. The proposed algorithms employ a Gaussian-PDF measure and an evidential measure respectively. In remote sensing application, segment-based approaches are used to extract more explicit information on spatial structure compared to pixel-based methods. Data from a single sensor may be insufficient to provide accurate description of a ground scene in image classification. Due to the redundant and complementary nature of multisensor data, a combination of information from multiple sensors can make reduce classification error rate. The Gaussian-PDF method defines a regional measure as the PDF average of pixels belonging to the region, and assigns a region into a class associated with the maximum of regional measure. The evidential fusion method uses two measures of plausibility and belief, which are derived from a mass function of the Beta distribution for the basic probability assignment of every hypothesis about region classes. The proposed methods were applied to the SPOT XS and ENVISAT data, which were acquired over Iksan area of of Korean peninsula. The experiment results showed that the segment-based method of evidential measure is greatly effective on improving the classification via multisensor fusion.

• Korean Journal of Remote Sensing
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• v.18 no.2
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• pp.107-116
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• 2002

A hybrid image segmentation algorithm is proposed which integrates edge-based and region-based techniques through the watershed algorithm. First, by using mean curvature diffusion coupled to min/max flow, noise is eliminated and thin edges are preserved. After images are segmented by watershed algorithm, the segmented regions are combined with neighbor regions. Region adjacency graph (RAG) is employed to analyze the relationship among the segmented regions. The graph nodes and edge costs in RAG correspond to segmented regions and dissimilarities between two adjacent regions respectively. After the most similar pair of regions is determined by searching minimum cost RAG edge, regions are merged and the RAG is updated. The proposed method efficiently reduces noise and provides one-pixel wide, closed contours.

• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.69-86
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• 1991

An unsupervised region based image segmentation algorithm implemented with a pyramid structure has been developed. Rather than depending on thraditional local splitting and merging of regions with a similarity test of region statistics, the algorithm identifies the homogenous and boundary regions at each level of pyramid, then the global parameters of esch class are estimated and updated with values of the homogenous regions represented at the level of the pyramid using the mixture distribution estimation. The image is then classified through the pyramid structure. Classification results obtained for both simulated and SPOT imagery are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.33-38
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• 2013

Smart phones that are equipped with various types of sensors can monitor human beings, and their social activities and environments. Smart phone sensing systems are inevitable to lose sensing data at a certain region. It is more severe effect on opportunistic sensing because this sensing scheme is designed to read values from sensors when the state of numberous users meets pre-defined conditions. In this paper, we suggested an estimation model of missing data considering features of smart phone sensing to solve lower quality of collected data. This proposed model does not only reflect a temporal and spatial correlation, but also give high priority to participants who provide high quality data to improve the accuracy of estimated values. The experimental results show that our scheme is more accurate than previous scheme.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.127-131
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• 1999

Typhoons were known by contributing to transporting plus heat or kinetic energy from equatorial region to midlatitude region. Due to the strong damage from typhoon, we acknowledged the theoretical study and the importance of accurate forecast about typhoon. In this study, typhoon forecasting system was developed to search the tracks of past typhoons or to display similar track of past typhoon in comparison with the path of current forecasting typhoon. It was programmed using Interactive Data Language(IDL), which was a complete computing environment for the interactive analysis and visualization of data. Typhoon forecasting system was also included satellite image and auxiliary chart. IR, Water Vapor, Visible satellite images helped users analyze an accurate forecast of typhoon. They were further refined the procedures for generating water vapor winds and gave an initial indication of their utility for numerical weather prediction(NWP), in particular for typhoon track forecasting where they could provide important information. They were also available for its utility in typhoon tracer or intensity.

• Proceedings of the KSRS Conference
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• v.2
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.31-33
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• 2004

Two receiving systems were established at the Asian Center for Research on Remote Sensing (ACRoRS) to receive remote sensing data from NOAA AVHRR and Terra/Aqua MODIS sensors in October 1997 and May 2001, respectively. The data, which has been received in the research center, are very important to support and promote the remote sensing research activities for global environmental issues in Asia. Since the day of the establishment, many research and applications, which used these data, have been conducted. The data sets have been provided to researchers and users in many countries in the region to conduct research, to strengthen the research collaboration and education.