• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.135-142
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• 2020

In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.497-502
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• 2003

Fingerprint classification plays a role of reduction of precise joining time and improvement of the accuracy in a large volume of database. Patterns of fingerprint are classified as 5 patterns : left loop, right loop, arch, whorl, and tented arch by numbers and the location of core point and delta point. The existing fingerprint classification is useful in a captured fingerprint image of core point and delta point using paper and ink. However, this system is unapplicable in modern Automatic Fingerprint Identification System (AFIS) because of problems such as size of input and way of input. To solve the problem, this study is to suggest the way of being able to improve accuracy of fingerprint by fingerprint classification based on the entropy of ridges using fingerprint captured mage of core point and prove this through the experiment.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.338-341
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• 2003

본 논문에서는 직선과 곡선으로 구성된 단순한 도면으로부터 곡선을 검출한 다음에 곡선을 원형 아크로 분할하는 방법을 제안한다. 본 논문의 방법에서는 먼저 선의 중심점을 찾은 다음에 연결된 중심점을 추적하여 선분을 검출한다. 그 다음에는 선분의 양 끝에서 선분의 방향을 이용하여 이웃한 선분을 검출하여 선분을 확장해 나간다. 선분을 확장한 다음에는 직선을 제거하고 곡선만 남긴 다음에 재귀적 분할 방법을 이용하여 곡선을 아크들의 집합으로 분할한다. 본 논문에서는 기존의 벡터화 소프트웨어와 벡터 기반 아크 분할 방법과 비교 실험을 수행하였다 실험 결과에 의하면 본 논문에서 제안된 방법이 기존의 방법에 비하여 교차점을 가지는 곡선에 대하여 보다 정확하게 아크로 분할하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.66-69
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• 1987

본 논문은 불특정화자의 한국어 단독음인식에 관한 연구로써 새로운 집단화 방법인 Modified-ISODATA 집단화방법을 제안한다.본 알고리즘의 목적은 종래의 ISODATA 알고리즘에서 외부 고립점 처리 및 분리과정을 단순화 하고, Lumping 과정을 제거하여 정확하고도 자동화된 집단의 중심점을 찾는 것이다. 본 알고리즘을 적용한 결과, 10명의 남성 화자와 4명의 여성 화자가 발음한 11개의 ltnt자음에 대하여, 최근에 발표된 Modified K-means 방법보다 좋은 인식율을 나타내어, 보다 정확한 집단의 중심점을 찾아 내었음을 입증해보였다.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.186-193
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• 2019

This article compares the weighted geometric median with the centroid, from the question why they use the centroid when they would find the single facility location(the weighted geometric median) which minimize the sum of weighted Euclidean distances in some text books and papers. Firstly, we show that the demand point whose volume of demand exceeds the half of total demand is the weighted geometric median differently from the centroid, and we examine the weighed geometric median when every demand point is located on a line. Meanwhile, we could simply see that the geometric median and the centroid are coincident in the special case when every demand point is located at a vertex of a regular polygon, and every volume of demand is equal. Furthermore, the geometric medians of convex tetragons could be simply attained unlike triangles.

• Korean Journal of Optics and Photonics
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• v.18 no.6
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• pp.375-382
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• 2007

The Shack-Hartmann wavefront sensor is composed of a lenslet array generating the spot images from which local slope is calculated and overall wavefront is measured. Generally the principle of wavefront reconstruction is that the spot centroid of each lenslet array is calculated from pixel intensity values in its subaperture, and then overall wavefront is reconstructed by the local slope of the wavefront obtained by deviations from reference positions. Hence the spot image of each lenslet array has to remain in its subaperture for exact measurement of the wavefront. However the spot of each lenslet array deviates from its subaperture area when a wavefront with large local slopes enters the Shack-Hartmann sensor. In this research, we propose a spot image searching method that finds the area of each measured spot image flexibly and determines the centroid of each spot in its area Also the algorithms that match these centroids to their reference points unequivocally, even if some of them are situated off the allocated subaperture, are proposed. Finally we verify the proposed algorithm with the test of a defocus measurement through experimental setup for the Shack-Hartmann wavefront sensor. It has been shown that the proposed algorithm can expand the dynamic range without additional devices.

• Progress in Medical Physics
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• v.22 no.1
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• pp.35-41
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• 2011

For overall system test, hidden-target test have been used using film which leads to inherent analysis error. The purpose of our study is to quantify this error and to propose gel dosimeter based verification technique for 3-dimensional target point error. The phantom was made for simulation of human head and this has ability to equip 10 gel-dosimeter. $BANGkit^{TM}$ which we are able to manufacture whenever it is needed as well as to easily change the container with different shapes was used as a gel dosimeter. The 10 targets were divided into two groups based on shapes of areas with a planned 50% isodose line. All treatment and analysis was performed three times using Novalis and $BrainSCAN^{TM}$. The target point error is $0.77{\pm}0.15mm$ for 10 targets and directional target point error in each direction is $0.54{\pm}0.23mm$, $0.37{\pm}0.08mm$, $0.33{\pm}0.10mm$ in AP (anterior-posterior), LAT (lateral), and VERT (vertical) direction, respectively. The result of less than 1 mm shows that the treatment was performed through each precise step in treatment procedure. In conclusion, the 3-dimensional target point verification technique can be one of the techniques for overall system test.

• Journal of Industrial Convergence
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• v.18 no.3
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• pp.35-43
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• 2020

This study was to identify the factors influencing the person centered care competency in nursing students. Data were conducted on 294 nursing students from September 1st to 25th 2019. The mean score of critical thinking disposition was 3.72, the interpersonal relationship was 3.90 and person centered care competency was 4.01. Nursing students with high degree of major satisfaction had higher level of critical thinking disposition, the interpersonal relationship and person centered care competency than students with low degree. Significant factors influencing person centered care competency were critical thinking disposition, the interpersonal relationship and grade which explained 33%. The programs that develop critical thinking disposition and interpersonal relationship are necessary for college nursing students in order to promote person centered care competency.

• Radiation Oncology Journal
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• v.18 no.2
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• pp.114-119
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• 2000

Purpose : To evaluate the e지ent and frequency of the inter- and intra-treatment isocenter deviations of the whole pelvis radiation field in using small bowel displacement system (SBDS). Methods and Materials : Using electronic portal imaging device (EPID), 302 postero-anterior 232 lateral portal images were prospectively collected from 11 patients who received pelvic radiation therapy (7 with cervix cancer and 4 with rectal cancer). All patients were treated in prone position with SBDS under the lower abdomen. Five metallic fiducial markers were placed on the image detection unit for the recognition of the isocenter and magnification. After aligning the bony landmarks of the EPID images on those of the reference image, the deviations of the isocenter were measured in right-left (RL), cranio-caudal (CC), and PA directions. Results : The mean inter-treatment deviation of the isocenter in each RL, CC, and PA direction was 1.2 mm ($\pm$ 1.6 mm), 1.0 mm ($\pm$3.0 mm), and 0.9 mm ($\pm$4.4 mm), respectively. Inter-treatment isocenter deviations over 5 mm and 10 mm in RL, CC, and PA direction were 2, 12, 24$\%$, and 0, 0, 5$\%$, respectively. Maximal deviation was detected in PA direction, and was 11.5 mm. The mean intratreatment deviation of the isocenter in RL, CC, and PA direction was 0 mm ($\pm$0.9 mm), 0.1 mm ($\pm$ 1.9mm), and 0 mm ($\pm$1.6 mm), respectively. All intra-treatment isocenter deviations over 5 mm in each direction were 0, 1, 1$\pm$, respectively. Conclusions : As the greatest and the most frequent inter-treatment deviation of the isocenter was along the PA direction, it is recommended to put more generous safety margin toward the PA direction on the lateral fields if clinically acceptable in pelvic radiotherapy with SBDD.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.12
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• pp.1437-1450
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• 1992

This paper describes the feature extraction of the interdigital regions of palm, and proposes a personal verification algorithm using the extracted features and the pattern types of those. The procedures of the feature extraction are as follows : first, the interdigital region is partitioned into several subregions, examining the phase of rigdes in each subregion, deciding the direction of that phase, and making the direction matrix of the region, we analyze this direction matrix to contain a feature pattern, and then, yield the first core. Second, applying the thinning to around the first core and tracing the thinned ridges, we yield the feature pattern types and second cores. Finally, the feature patterns coordinates included all of them are built. Then, distances and directions from each second core reaching to all the others are yielded from that coordinates. These informations are used to make a feature parameter. In our verification algorithm, such pattern types, the numbers of feature patterns, theses positions and feature parameters are used to analyze.