• Journal of Korean Dental Science
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• v.12 no.1
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• pp.20-28
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• 2019

Purpose: This study was performed to evaluate the effect of voxel size on the accuracy of landmark identification in cone-beam computed tomography (CBCT) images. Materials and Methods: CBCT images were obtained from 15 dry human skulls with two different voxel sizes; 0.39 mm and 0.10 mm. Three midline landmarks and eight bilateral landmarks were identified by 5 examiners and were recorded as three-dimensional coordinates. In order to compare the accuracy of landmark identification between large and small voxel size images, the difference between best estimate (average value of 5 examiners' measurements) and each examiner's value were calculated and compared between the two images. Result: Landmark identification errors showed a high variability according to the landmarks in case of large voxel size images. The small voxel size images showed small errors in all landmarks. The landmark identification errors were smaller for all landmarks in the small voxel size images than in the large voxel size images. Conclusion: The results of the present study indicate that landmark identification errors could be reduced by using smaller voxel size scan in CBCT images.

• The korean journal of orthodontics
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• v.49 no.1
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• pp.41-48
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• 2019

Objective: This in-vivo study aimed to compare landmark identification errors in anteroposterior (AP) and posteroanterior (PA) cephalograms generated from cone-beam computed tomography (CBCT) scan data in order to examine the feasibility of using AP cephalograms in clinical settings. Methods: AP and PA cephalograms were generated from CBCT scans obtained from 25 adults. Four experienced and four inexperienced examiners were selected depending on their experience levels in analyzing frontal cephalograms. They identified six cephalometric landmarks on AP and PA cephalograms. The errors incurred in positioning the cephalometric landmarks on the AP and PA cephalograms were calculated by using the straight-line distance and the horizontal and vertical components as parameters. Results: Comparison of the landmark identification errors in CBCT-generated frontal cephalograms revealed that landmark-dependent differences were greater than experienceor projection-dependent differences. Comparisons of landmark identification errors in the horizontal and vertical directions revealed larger errors in identification of the crista galli and anterior nasal spine in the vertical direction and the menton in the horizontal direction, in comparison with the other landmarks. Comparison of landmark identification errors between the AP and PA projections in CBCT-generated images revealed a slightly higher error rate in the AP projections, with no inter-examiner differences. Statistical testing of the differences in landmark identification errors between AP and PA cephalograms showed no statistically significant differences for all landmarks. Conclusions: The reproducibility of CBCT-generated AP cephalograms is comparable to that of PA cephalograms; therefore, AP cephalograms can be generated reliably from CBCT scan data in clinical settings.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.164-169
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• 2009

As one of the most interesting scenes, landmarks constitute a large percentage of the vast amount of scene images available on the web. On the other hand, a specific "landmark" usually has some characteristics that distinguish it from surrounding scenes and other landmarks. These two observations make the task of accurately estimating geographic information from a landmark image necessary and feasible. In this paper, we propose a method to identify landmark location by means of landmark recognition in view of significant viewpoint, illumination and temporal variations. We use GPS-based clustering to form groups for different landmarks in the image dataset. The images in each group rather fully express the possible views of the corresponding landmark. We then use a combination of edge and color histogram to match query to database images. Initial experiments with Zubud database and our collected landmark images show that is feasible.

• The korean journal of orthodontics
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• v.49 no.1
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• pp.32-40
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• 2019

Objective: Precise identification of landmarks on posteroanterior (PA) cephalograms is necessary when evaluating lateral problems such as facial asymmetry. The aim of the present study was to investigate whether the use of lateral (LA) cephalograms can reduce errors in landmark identification on PA cephalograms. Methods: Five examiners identified 16 landmarks (Cg, N, ANS, GT, Me, RO, Lo, FM, Z, Or, Zyg, Cd, NC, Ms, M, and Ag) on 32 PA cephalograms with and without LA cephalograms at the same time. The positions of the landmarks were recorded and saved in the horizontal and vertical direction. The mean errors and standard deviation of landmarks location according to the use of LA cephalograms were compared for each landmark. Results: Relatively small errors were found for ANS, Me, Ms, and Ag, while relatively large errors were found for N, GT, Z, Or, and Cd. No significant difference was found between the horizontal and vertical errors for Z and Or, while large vertical errors were found for N, GT, and Cd. The value of identification error was lower when the landmarks were identified using LA cephalograms. Statistically significant error reductions were found at N and Cd with LA cephalograms, especially in the vertical direction. Conclusions: The use of LA cephalograms during identification of landmarks on PA cephalograms could help reduce identification errors.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1606-1611
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• 2005

The goal of this paper is to develop a self localization of mobile robot using UHF RFID landmark. We present landmark, a location sensing archetype system that uses UHF Radio Frequency Identification (UHF RFID) technology for locating objects inside buildings. The major advantage of landmark is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that passive UHF RFID is a viable and cost-effective candidate for indoor location sensing. We conduct a series of experiments to evaluate performance of the positioning of the landmark System. In the standard setup, we place RF Reader which has two antennas and 25 tags in our lab. This research uses the assumption-based coordinates (ABC) algorithm[3] for determining the localization of robot. Also, we show how Radio Frequency Identification (UHF RFID) can be used in robot-assisted indoor navigation for the visually impaired. The experiments illustrate that passive UHF RFID tags can act as reliable landmark that trigger local navigation behaviors to achieve global navigation objectives.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.418-420
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• 1993

In this paper, we proposed a new FMS Landmark recognition algorithm using color images. Firstly, a NTSC image fame is captured, and then it is converted to a field image in order to reduce the image blurring from the AGV motion. Secondly, the landmark is detected via the comparison of the color vectors of image pixels with the landmark color. Finally, the identification of FMS landmark is executed using a newly designed landmark pattern with a set of reference points. The landmark pattern is normalized against its translation, rotation, and scaling. And then, its vertical projection data are fisted for the pattern classification using the standard data set. Experimental results show that our scheme performs well.

• International Journal of Contents
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• v.2 no.3
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• pp.27-32
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• 2006

We present an effective algorithm for automatic tracing of retinal vessel structure and vascular landmark extraction of bifurcations and ending points. In this paper we deal with vascular patterns from RGB images for personal identification. Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing in RGB images has many problems which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting vascular structure using eight directional information, and extracting retinal vascular structure, and Vascular Landmark Extraction by extracting bifurcations and ending points. The results of automatic retinal vessel extraction using jive different thresholds applied 34 eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only robust and accurate vessel tracing but also vascular landmarks according to thresholds.

• The korean journal of orthodontics
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• v.32 no.2 s.91
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• pp.79-89
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• 2002

The purpose of this study is to evaluate the reproducibility and errors in landmark identification of conventional lateral cephalometric radiography and digital lateral cephalometric radiography. Fifteen conventional lateral cephalometric radiographs and fifteen digital lateral cephalometric radiographs were selected in adults with no considerations on sex and craniofacial forms. Each landmark was identified and expressed as the coordinate (x, y). The landmarks were classified into 3 groups. The landmarks of the first identification was T1, identification after one week was T2, and identification after one month was T3. The mean and standard deviation of identification errors between replicates were calculated according to the x and y coordinates. The errors between first identification and second identification were expressed as T2-T1(x), T2-T1(y) and those between first identification and third identification were expressed as T3-T1(x), T2-T1(y). Each was divided into conventional lateral cephalometric radiography and digital lateral cephalometric radiography. The independent t- test was used for statistical analysis of identification errors for the evaluation of reproducibility. The results of this study were as follows ; 1. Generally, the mean and standard deviation of landmark identification errors in digital lateral cephalometric radiography was smaller than those of conventional lateral cephalometric radiography. 2. Only a few landmarks showed statistically significant difference in identification error between conventional lateral cephalometric radiography and digital lateral cephalometric radiography. 3. The enhancement of image quality didn't guarantee decrease in landmark identification error and didn't affect tendency of landmark identification error.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.3
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• pp.245-254
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• 2021

The aim of this study was to evaluate the accuracy of 3 different automatic landmark identification programs on lateral cephalgrams and the clinical acceptability in pediatric dentistry. Sixty digital cephalometric radiographs of 7 to 12 years old healthy children were randomly selected. Fourteen landmarks were chosen for assessment and the mean of 3 measurements of each landmark by a single examiner was defined as the baseline landmarks. The mean difference between an automatically identified landmark and the baseline landmark was measured for each landmark on each image. The total mean difference of 3 automatic programs compared to the baseline landmarks were 2.53 ± 1.63 mm. Errors among 3 programs were not significantly different for 12 of 14 landmarks except Orbitale and Gonion. The automatic landmark identification programs showed significant higher mean detection errors than the manual method. The programs couldn't be used as the 1st tool to replace human examiners. But considering short consuming time, these results indicate that all 3 programs have sufficient validity to be used in pediatric dental clinic.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1183-1185
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• 2012

본 논문은 최근 항만 터미널 장치장 내 무인 자동화가 빠르게 연구 진행되고 있는 가운데 다양한 자동화 기술들이 제공되고 있다. 우리는 장치장 내 효과적인 작업 효율을 위하여 RFID(Radio Frequency Identification)를 이용한 무인이송장비(YT:Yard Tractor)의 정지위치 인식 시스템을 제안한다. 제안된 시스템은 장치장내에서 YT의 정지하고자 하는 장소에서 RFID의 신호와 LANDMARK를 이용하여 정지한다. 정지 위치 장소에 두 개의 RFID태그를 설치하여 작업영역 및 정지위치를 각각의 태그 정보에 포함시킨다. YT는 정지장소에 도달하면 지정된 작업 영역인지 태그 정보를 통해 확인하고, 확인 후 정지위치정보를 포함하는 태그와 LANDMARK를 통해 정확한 위치에 정지한다.