• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.25-31
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• 2004

To obtain the 3-D coordinates of the urban roads from aerial images, the accurate matching technique in road areas is required. In this paper, we suggest the relational matching method that is performed by comparison of relationships of road pavement markings after they are extracted from aerial images using geometric properties and spatial relationships of the pavement markings. Relational matching requires not only high level description of features but also the solution for inexact matching problems. In addition, it needs a lot of tests for the reliable final result. In this research, we described features as calculating geometric properties of the pavement markings, suggested the solution for inextact matching problems, and performed tests to decide whether the result is acceptable or not, which use the property that road areas are flat. In order to evaluate the accuracy of matching, we made a visual evaluation and compared the result of this technique with those measured by analytical photogrammetry.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.811-816
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• 2011

In this paper, we analysis to consider the performance of PSPM (Phase Shift Pulse-position Modulation), the one of the low power communication technique, in near-field underwater sound channel by sea trial. PSPM is a QPSK(Quadrature Phase Shift Keying) modulation combined with PPM(Pulse Position Modulation) for low power communication in WBAN(Wireless Body Area Network). It is known that the bandwidth efficiency of PSPM is lower than conventional PSK but the power efficiency increases. In this paper, we will analyze the BER performance of PSPM using data acquired from the sea trials. The BER of QPSK was $6.04{\times}10^{-2}$, PSPM was $3.5{\times}10^{-1}$. Also, PSNR of QPSK was 9.37 dB and in case of PSPM was 9.11 dB.

• 한국지구물리탐사학회:학술대회논문집
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• 2004.08a
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• pp.49-69
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• 2004

One of the important roles of geophysical exploration in archeological survey may be to provide the subsurface information for effective and systematic excavations of historical remains. Ground Penetrating Radar (GPA) can give us images of shallow subsurface structure with high resolution and is regarded as a useful and important technology in archeological exploration. Since the buried cultural relics are the three-dimensional (3-D) objects in nature, the 3-D or areal survey is more desirable in archeological exploration. 3-D GPR survey based on the very dense data in principle, however, might need much higher cost and longer time of exploration than the other geophysical methods, thus it could have not been applied to the wide area exploration as one of routine procedures. Therefore, it is important to develop an effective way of 3-D GPR survey. In this study, we applied 3-D GPR method to investigate the possible historical remains of Baekje Kingdom at Gatap-Ri, Buyeo city, prior to the excavation. The principal purpose of the investigation was to provide the subsurface images of high resolution for the excavation of the surveyed area. Besides this, another purpose was to investigate the applicability and effectiveness of the continuous data acquisition system which was newly devised for the archeological investigation. The system consists of two sets of GPR antennas and the precise measurement device tracking the path of GPR antenna movement automatically and continuously Besides this hardware system, we adopted a concept of data acquisition that the data were acquired arbitrary not along the pre-established profile lines, because establishing the many profile lines itself would make the field work much longer, which results in the higher cost of field work. Owing to the newly devised system, we could acquire 3-D GPR data of an wide area over about $17,000 m^2$ as a result of the just two-days field work. Although the 3-D GPR data were gathered randomly not along the pre-established profile lines, we could have the 3-D images with high resolution showing many distinctive anomalies which could be interpreted as old agricultural lands, waterways, and artificial structures or remains. This case history led us to the conclusion that 3-D GPR method can be used easily not only to examine a small anomalous area but also to investigate the wider region of archeological interests. We expect that the 3-D GPR method will be applied as a one of standard exploration procedures to the exploration of historical remains in Korea in the near future.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Spatial Information Research
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• v.12 no.4 s.31
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• pp.299-305
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• 2004

According to the facility of effective search and user-friendly access to various spatial data by building GIS, the demand for application of information and social effect has been increased. To meet such domestic demands, it has become necessary to develop local, regional, and global SDI(Spatial Data Infrastructure) which can support discovery, access, and use of spatial information in the decision-making process. Many developed countries are implementing and managing GSDI in accordance with their state and purpose. There are two typical international cases; U.S. Geospatial One-Stop and European Geo-Portal. These systems are observed the international standards so they provide standardization and interoperability of GI. In domestic cases, however, each sector is managing separately geospatial data management systems. From this point of view, this paper proposed implementation approaches of GOS that can provide interchange of geospatial information between supplier and user. This paper focused on standardization, considered technical and political factors and analyzed two cases of GOS such as U.S. and Europe cases into our spatial information environments. It is possible to search and access geospatial data effectively by introducing GOS. In addition, it is possible to promote popularization of geospatial information and development of GIS industy.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.741-747
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• 2009

For construction of 3D virtual city models, airborne digital cameras, laser scanners, multi-oblique photograph systems and other devices are currently being used. With such advanced techniques, precise 3D spatial information can be collected and high quality 3D city models can be built in a considerably large area. The 3D spatial information to be built has to provide the latest information that quickly reflects the causes of any change due to urban development. In this study, a UAV photogrammetric method using low cost UAV and digital camera was proposed to acquire and update 3D spatial information effectively on small areas where information continuously change. In the proposed UAV photogrammetric method, the elements of interior orientation were acquired through camera calibration and the vertical and oblique photographs were taken at 9 points and the 3D drawing of ground control points and buildings was performed using 20 images among the pictured images. This study also analyzed the accuracy of the proposed method comparing with ground survey data and digital map in order to examine whether the method can be used in on-demand 3D spatial information update on relatively small areas.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.583-598
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• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.65-74
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• 2021

In order to efficiently inspect rapidly increasing old tunnels in many well-developed countries, many inspection methodologies have been proposed using imaging equipment and image processing. However, most of the existing methodologies evaluated their performance on a clean concrete surface with a limited area where other objects do not exist. Therefore, this paper proposes a 6-step framework for tunnel crack detection deep learning model development. The proposed method is mainly based on negative sample (non-crack object) training and Cascade Mask R-CNN. The proposed framework consists of six steps: searching for cracks in images captured from real tunnels, labeling cracks in pixel level, training a deep learning model, collecting non-crack objects, retraining the deep learning model with the collected non-crack objects, and constructing final training dataset. To implement the proposed framework, Cascade Mask R-CNN, an instance segmentation model, was trained with 1561 general crack images and 206 non-crack images. In order to examine the applicability of the trained model to the real-world tunnel crack detection, field testing is conducted on tunnel spans with a length of about 200m where electric wires and lights are prevalent. In the experimental result, the trained model showed 99% precision and 92% recall, which shows the excellent field applicability of the proposed framework.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.34-39
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• 2018

This research was conducted to estimate moisture content in cucurbitaceae seedlings, such as cucumber and watermelon, using hyperspectral imagery. Using a hyperspectral image acquisition system, the reflectance of leaf area of cucumber and watermelon seedlings was calculated after providing water stress. Then, moisture content in each seedling was measured by using a dry oven. Finally, using reflectance and moisture content, the moisture content estimation models were developed by PLSR analysis. After developing the estimation models, performance of the cucumber showed 0.73 of $R^2$, 1.45% of RMSE, and 1.58% of RE. Performance of the watermelon showed 0.66 of $R^2$, 1.06% of RMSE, and 1.14% of RE. The model performed slightly better after removing one sample from cucumber seedlings as outlier and unnecessary. Hence, the performance of new model for cucumber seedlings showed 0.79 of $R^2$, 1.10% of RMSE, and 1.20% of RE. The model performance combined with all samples showed 0.67 of $R^2$, 1.26% of RMSE, and 1.36% of RE. The model of cucumber showed better performance than the model of watermelon. This is because variables of cucumber are consisted of widely distributed variation, and it affected the performance. Further, accuracy and precision of the cucumber model were increased when an insignificant sample was eliminated from the dataset. Finally, it is considered that both models can be significantly used to estimate moisture content, as gradients of trend line are almost same and intersected. It is considered that the accuracy and precision of the estimating models possibly can be improved, if the models are constructed by using variables with widely distributed variation. The improved models will be utilized as the basis for developing low-priced sensors.