• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.208-211
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• 2004

Landmark matching is one of an important algorithm for navigation of satellite images. This paper proposes a fast landmark matching algorithm using a MGLI (Moving Guide-Line Image). For searching the matched point between the landmark chip and a part of image, correlation matrix is used generally, but the full-sized correlation matrix has a drawback requiring plenty of time for matching point calculation. MGLI includes thick lines for fast calculation of correlation matrix. In the MGLI, width of the thick lines should be determined by satellite position changes and navigation error range. For the fast landmark matching, the MGLI provides guided line for a landmark chip we want to match, so that the proposed method should reduce candidate areas for correlation matrix calculation. This paper will show how much time is reduced in the proposed fast landmark matching algorithm compared to general ones.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.297-309
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• 2007

The first Korean geostationary weather satellite, Communications, Oceanography and Meteorology Satellite (COMS) will be launched in 2008. The ground station for COMS needs to perform geometric correction to improve accuracy of satellite image data and to broadcast geometrically corrected images to users within 30 minutes after image acquisition. For such a requirement, we developed automated and fast geometric correction techniques. For this, we generated control points automatically by matching images against coastline data and by applying a robust estimation called RANSAC. We used GSHHS (Global Self-consistent Hierarchical High-resolution Shoreline) shoreline database to construct 211 landmark chips. We detected clouds within the images and applied matching to cloud-free sub images. When matching visible channels, we selected sub images located in day-time. We tested the algorithm with GOES-9 images. Control points were generated by matching channel 1 and channel 2 images of GOES against the 211 landmark chips. The RANSAC correctly removed outliers from being selected as control points. The accuracy of sensor models established using the automated control points were in the range of $1{\sim}2$ pixels. Geometric correction was performed and the performance was visually inspected by projecting coastline onto the geometrically corrected images. The total processing time for matching, RANSAC and geometric correction was around 4 minutes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1157-1164
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• 2006

In this paper, we proposed a method for measuring accurate positions and sizes of package and balls in a micro BGA. To find defects of BGA accurately, we focused on finding positions of package and balls. After labeling, we detected connected components of package and balls using feature parameters. After the detection of package component, we measured position and size of package by employing rectangular model which was constructed by the package information. After the detection of the ball components, we measured positions and diameters of balls by employing circular models which were constructed by the ball informations. We did calibration based on landmarks to measure real length, and we compared the measured results with the SEM data. Finally, we found that the accuracy of the proposed method is 94% in terms of ball's radius.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.99-106
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• 2022

In this paper, We propose a method for identifying objects by setting inscriptions and landmarks of dogs. The phenomenon of abandoning dogs is on the rise, and the number of abandoned individuals is also rapidly increasing. These abandoned dogs are becoming wild animals, causing a lot of damage to people's daily life, causing serious problems. As a solution to this problem, the animal registration system is being implemented, but there is a phenomenon that some dog owners avoid the registration method that inserts a chip, so the complete registration system is not settled. When registering a dog, removing the avoidance of dog owners will help establish the companion animal registration system. In this paper, we present a technique to identify objects by setting inscriptions and landmarks of dogs so that dog owners can register their dogs in a friendly way to eliminate this avoidance phenomenon.