• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.4
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• pp.26-35
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• 2003

For the recognizing system to be classified the same or different images in the nature the rotation, scale and transition invariant features is to be necessary. There are many investigations to get the feature for the recognition system and the log-polar transform which is to be get the invariant feature for the scale and rotation is used. In this paper, we suggested the character recognition methods which are used the centroid method and the log-polar transform with the interpolation to get invariant features for the character recognition system and obtained the results of the above 50% differential ratio for the character features. And we obtained the about 90% recognition ratio from the suggested character recognition system using the BPEJTC which is used the invariant feature from the Mellin transform method for the reference image. and can be recognized the scaled and rotated input character. Therefore, we suggested the image character recognition system using the Mellin transform method and the BPEJTC is possible to recognize with the invariant feature for rotation scale and transition.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1133-1148
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• 2019

Tree growth and vitality in forest shows seasonal changes. So, in order to detect forest damage accurately, we have to use satellite images before and after damages taken at the same season. However, temporal resolution of high or medium resolution images is very low,so it is not easy to acquire satellite images of the same seasons. Therefore, in this study, we estimated spectral information of the same DOY using time-series Landsat images and used the estimates as reference values to assess forest damages. The study site is Hwasun, Jeollanam-do, where forest damage occurred due to hail and drought in 2017. Time-series vegetation index (NDVI, EVI, NDMI) maps were produced using all Landsat 8 images taken in the past 3 years. Daily normal vegetation index maps were produced through cloud removal and data interpolation processes. We analyzed the difference of daily normal vegetation index value before damage event and vegetation index value after event at the same DOY, and applied the criteria of forest damage. Finally, forest damage map based on daily normal vegetation index was produced. Forest damage map based on Landsat images could detect better subtle changes of vegetation vitality than the existing map based on UAV images. In the extreme damage areas, forest damage map based on NDMI using the SWIR band showed similar results to the existing forest damage map. The daily normal vegetation index map can used to detect forest damage more rapidly and accurately.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.275-285
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• 2017

National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.209-221
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• 2009

Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variaty of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.259-266
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• 2003

Non-rigid registration between different modality images with shape deformation can be used to diagnosis and study for inter-patient image registration, longitudinal intra-patient registration, and registration between a patient image and an atlas image. This paper proposes a hierarchical registration method using bodily tissue based segmentation for registration between color images and CT images of the Visible Human leg areas. The cross-sectional color images and the axial CT images are segmented into three distinctive bodily tissue regions, respectively: fat, muscle, and bone. Each region is separately registered hierarchically. Bounding boxes containing bodily tissue regions in different modalities are initially registered. Then, boundaries of the regions are globally registered within range of searching space. Local boundary segments of the regions are further registered for non-rigid registration of the sampled boundary points. Non-rigid registration parameters for the un-sampled points are interpolated linearly. Such hierarchical approach enables the method to register images efficiently. Moreover, registration of visibly distinct bodily tissue regions provides accurate and robust result in region boundaries and inside the regions.

• Journal of Advanced Navigation Technology
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• v.17 no.5
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• pp.475-483
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• 2013

In this paper, the performances of modeling methods for combining corrections from multiple reference stations for network user were compared and analyzed. The longer the distance between reference station and user is, the more the GPS errors are decorrelated. Based on this point, multiple corrections from reference stations which is constituting a network should be combined properly to be applied for user observation to eliminate GPS errors. There are many widely used conventional modeling methods and they are applied for Compact Network RTK users and user position accuracy is predicted by using residual errors in observation of user. Compact Network RTK is a technique of generating corrections which was developed by Seoul National University. As a result, the horizontal and vertical accuracies were within about 5 cm and 7 cm respectively with 95 % probability for all conventional modeling methods. In addition, we analyzed condition for reference station constellation for modeling method using height information.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.90-104
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• 2015

The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.170-181
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• 2015

A research on extracting croplands located nearby coastal areas using the spatial information data sets is the important task for managing the agricultural products in coastal areas. This research aims to extract the various croplands(croplands on mountains and croplands on plain areas) located nearby coastal areas using the KOMPSAT-2 imagery, the high-resolution satellite imagery, and the airborne topographic LiDAR(Light Detection And Ranging) data acquired in coastal areas of Uljin, Korea. Firstly, the NDVI(Normalized Difference Vegetation Index) imagery is generated from the KOMPSAT-2 imagery, and the vegetation areas are extracted from the NDVI imagery by using the appropriate threshold. Then, the DSM(Digital Surface Model) and DEM(Digital Elevation Model) are generated from the LiDAR data by using interpolation method, and the CHM(Canopy Height Model) is generated using the differences of the pixel values of the DSM and DEM. Then the plain areas are extracted from the CHM by using the appropriate threshold. The low slope areas are also extracted from the slope map generated using the pixel values of the DEM. Finally, the areas of intersection of the vegetation areas, the plain areas and the low slope areas are extracted with the areas higher than the threshold and they are defined as the croplands located nearby coastal areas. The statistical results show that 85% of the croplands on plain areas and 15% of the croplands on mountains located nearby coastal areas are extracted by using the proposed methodology.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• The Journal of Engineering Geology
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• v.29 no.3
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• pp.251-264
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• 2019

The displacement monitoring of unstable block at the rock slope located in the Cheonbuldong valley of Seoraksan National Park was carried out using Terrestrial LiDAR. The rock slopes around Guimyeonam and Oryeon waterfall where rockfall has occurred or is expected to occur are selected as the monitoring section. The displacement monitoring of unstable block at the rock slope in the selected area was performed 5 times for about 7 months using Terrestrial LiDAR. As a result of analyzing the displacement based on the Terrestrial LiDAR scanning, the error of displacement was highly influenced by the interpolation of the obstruction section and the difference of plants growth. To minimize the external influences causing the error, the displacement of unstable block should be detected at the real scanning point. As the result of analyzing the displacement of unstable rock at the rock slope using the Terrestrial LiDAR data, the amount of displacement was very small. Because the amount of displacement was less than the range of error, it was difficult to judge the actual displacement occurred. Meanwhile, it is important to select a section without vegetation to monitor the precise displacement of unstable rock at the rock slope using Terrestrial LiDAR. Also, the PointCloud removal and the mesh model analysis in a vegetation section were the most important work to secure reliability of data.