• ICROS
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• v.21 no.4
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• pp.27-33
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• 2015

단일 센서 기반의 표적 탐지 문제에서 센서의 한계 요소에 의해 탐지 성능이 제한된다. 따라서, 최근 단일 센서 기반의 표적 탐지 성능을 향상시키기 위한 방안으로 각 센서의 강점을 효과적으로 융합하는 다중 센서 정보 융합 기반의 표적 탐지 기법에 대한 연구가 활발히 진행되고 있다. 센서 정보 융합을 위해서는 각 센서별 영상 획득, 각 영상의 기하학적 정합, 센서 정보 융합 기반의 표적 탐지 기술이 필요하며, 본 논문에서는 이에 대한 기술 및 개발 동향을 소개한다.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.177-186
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• 2005

In this Paper. we propose vision-based camera localization technique using 3D information which is created by mapping of DEM and mountain image. Typically, image features for localization have drawbacks, it is variable to camera viewpoint and after time information quantify increases . In this paper, we extract invariance features of geometry which is irrelevant to camera viewpoint and estimate camera extrinsic Parameter through accurate corresponding Points matching by Proposed similarity evaluation function and Graham search method we also propose 3D information creation method by using graphic theory and visual clues, The Proposed method has the three following stages; point features invariance vector extraction, 3D information creation, camera extrinsic Parameter estimation. In the experiments, we compare and analyse the proposed method with existing methods to demonstrate the superiority of the proposed methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.15-21
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• 2009

Deformity detection in a Light Emitting Diode (LED) is an important aspect for improving its quality. These LED deformities can be checked through several methods. This paper details the automatic deformity detection inspection system of a LED using the LabVIEW Builder 3.6 software. This software has a graphical user interface which makes it easy to observe and modify the behavior of its element. The LabVIEWs essential elements are also presented and explained aside from its image acquisition system. Details on how to build an inspection system and how to implement vision inspection algorithm which mainly consists of edge detection, geometry point location, and distance measurement are included in this paper.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.419-426
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• 2005

Recently the interest in coast area has been increased in the view of management and usage of national territory. Rapid coastal development has caused directly or indirectly coastline changes which may make environmental problems or threaten the nearby residents' livelihood. CORONA was one of the US satellite reconnaissance programs, and it's imagery provides informations about past coastline with high resolution. In this study, we applied rigorous geo-referencing algorithm to CORONA imagery in order to generate the mosaic image of the East coast area of 1969 with 20m accuracy. This old era CORONA mosaic image was compared with SPOT image of 2005, and the coastline changes were analyzed. We were able to ascertain considerable erosion and accumulation in some parts of study area. erosion area which is calculated from imagery is $0.32\;km^2$ from Kosung to Kangnung. Results of coastline change detection can provide useful information for related studies.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.929-938
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• 2004

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with previously estimated pitch pose angle by the stereo geometry. Also, since we have an advantage that we can utilize two images acquired at the same time, we can increase overall recognition performance by decision-level fusion. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the yaw pose transform, and the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model. Also, by using stereo camera system we achieved an increased recognition rate 5.24% more for the case of upper face pose, and 3.34% more by decision-level fusion.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.447-456
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• 2003

This study investigated the method for obtaining 3-dimensional terrain information on inaccessable areas by evaluating geometric accuracy of the EOC pass image and scene image acquired from the KOMPSAT-1 satellite. For this purpose, the following four experiments were conducted to evaluate the accuracy of the KOMPSAT-1 EOC satellite data. 1) Calculation of ground coordinates by using ancillary data and image coordinates on Level 1R that were processed by the pre-processing system of KOMPSAT-1. 2) Calculation of 3-dimensional ground coordinates from the ground coordinates of stereo images calculated by using ancillary data, based on space intersections. 3) Execution of bundle adjustment by using GCP (Ground Control Point) extracted in a part of the stereo pass image (KOMPSAT-1 EOC, 1 scene size); and then, evaluation of the ground coordinates from the calculated exterior orientation. 4) Evaluation of accuracy by applying the exterior orientation calculated from 3) To the whole pass image.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1235-1243
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• 2021

Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.

• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.99-106
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• 2003

The shoreline changes were observed and analysed using the video image by a remote unmanned automatic camera monitoring system installed at Haeundae beach of Busan City. In order to analyse quantitatively the shoreline changes caused by waves and tides, the image averaging technique and the rectification technique for obliquely acquired image were applied to the video image during the typhoon Bart in September, 1999. The results showed that the camera monitoring system can be used as a very cost effective and efficient tool for monitoring shorelines which change continuously due to waves and tides.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.1
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• pp.81-90
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• 2004

Because satellite images include geometry distortions according to photographing conditions and sensor property, and their spatial and radiational resolution and spectrum resolution are different, it is so difficult to make a precise results of analysis. For comparing more than two images, the precise geometric corrections should be preceded because it necessary to eliminate systematic errors due to basic sensor information difference and non-systematic errors due to topographical undulations. In this study, we did sensor modeling using satellite sensor information to make a basic map of change detection for artificial topography. We eliminated the systematic errors which can be occurred in photographing conditions using GCP and DEM data. The Kompsat EOC images relief could be reduced by precise rectification method. Classifying images which was used for change detections by city and forest zone, the accuracy of the matching results are increased by 10% and the positioning accuracies also increased. The result of change detection using basic map could be used for basic data fur GIS application and topographical renovation.