• 대한원격탐사학회지
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• 제31권4호
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• pp.293-302
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• 2015

Water body extraction is significant for flood disaster monitoring using satellite imagery. Conventional methods have focused on finding an index, which highlights water body and suppresses non-water body such as vegetation or soil area. The Normalized Difference Water Index (NDWI) is typically used to extract water body from satellite images. The drawback of NDWI, however, is that some man-made objects in built-up areas have NDWI values similar to water body. The objective of this paper is to propose a new method that could extract correctly water body with built-up areas in before and after images of flood. We first create a two-element feature vector consisting of NDWI and a Near InfRared band (NIR) and then select a training site on water body area. After computing the mean vector and the covariance matrix of the training site, we classify each pixel into water body based on Mahalanobis distance. We also register before and after images of flood using outlier removal and triangulation-based local transformation. We finally create a change map by combining the before-flooding water body and after-flooding water body. The experimental results show that the overall accuracy and Kappa coefficient of the proposed method were 97.25% and 94.14%, respectively, while those of the NDWI method were 89.5% and 69.6%, respectively.

• 한국의류산업학회지
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• 제22권1호
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• pp.55-65
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• 2020

Smart photonic clothing integrates light emitting technology inside and outside of the garment and integrates it as a fashion product. It expresses digital color that radiates light outside the body that expands the functionality of the clothing as well as makes new and various attempts visually. It is also is gradually expanding into a new area of fashion. LED, one of the digital color output devices, is a light emitting device that is suitable for presenting consumer customized designs in that the patterns and colors of clothes can be modified as desired by utilizing computer technology such as program coding. LED technology that can realize various digital colors is actively applied in various industrial design fields, but there are few previous studies on smart clothes using LED color in Korean fashion fields. Therefore, this study develops a prototype of a customized LED smart photonic garment that allows the user to directly participate in the color implementation of clothing and select a digital color suitable for the desired function. The LED module was designed to be detachable from clothing and made using a 256-pixel LED matrix. Various coding patterns of the LED were designed using the coding change of Arduino program.

• 한국전기전자재료학회논문지
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• 제16권9호
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• pp.812-815
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• 2003

In this study, the MgO thin-film passivation layer was adopted to protect passive matrix organic light emitting diode(PMOLED) with the cathode separator from moisture and oxygen. Using the substrate rotate and tilt technique during the deposition, the organic and cathode layers were perfectly covered with MgO. And then, we analyzed the difference of the current-voltage and luminescence characteristics between passivated OLED of the MgO and non-passivated OLED. It was found that the number of dark spot generated from the degradated pixel was decreased owing to the Mgo thin-film passivation layer using the tilt ＆ rotate technique. And the half-life time passivated OLED was improved two times more. Thus, the MgO could be vaccum-deposited under the low temperature and had a merit that the organic layer was not much affected. We can consider that MgO thin film passivation method can be adopted to protect the OLED from moisture and oxygen and can offer the enhancement of lifetime.

• 전자공학회논문지
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• 제54권6호
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• pp.123-133
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• 2017

본 논문에서는 LED 디스플레이 시스템의 동적인 구동방식에서 LPM 모듈의 구성에 관계없이 휘도구현 비트를 16비트 이내, 휘도 구현 펄스를 512개 이내에서 최적의 플리커 프리 제어 알고리즘을 개발하고 이 알고리즘을 이용하여 디스플레이 제어장치를 구현하였다. 구현방법으로는 완전한 색 표현을 위한 기존의 시프트-래치 방법을 변형하여 여러 번의 시프트-래치를 수행하게 하여 스캔횟수를 늘림으로써 리플레시율을 증가시키는 방법을 사용하였다. 그 결과로 기존의 LED 디스플레이 시스템은 리플레시율이 240~480[Hz]를 수행하지만 제안된 방법을 사용하면 리플레시율을 2,040[Hz] 이상으로 높게 구현할 수 있기 때문에 플리커 현상을 감지할 수 없게 된다.

• Journal of Information Display
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• 제6권4호
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• pp.26-34
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• 2005

In this paper, a new rectification scheme to transform the uncalibrated stereo image pair into the calibrated one is suggested and its performance is analyzed by applying this scheme to the reconstruction of the intermediate views for multi-view stereoscopic display. In the proposed method, feature points are extracted from the stereo image pair by detecting the comers and similarities between each pixel of the stereo image pair. These detected feature points, are then used to extract moving vectors between the stereo image pair and the epipolar line. Finally, the input stereo image pair is rectified by matching the extracted epipolar line between the stereo image pair in the horizontal direction. Based on some experiments done on the synthesis of the intermediate views by using the calibrated stereo image pairs through the proposed rectification algorithm and the uncalibrated ones for three kinds of stereo image pairs; 'Man', 'Face' and 'Car', it is found that PSNRs of the intermediate views reconstructed from the calibrated images improved by about 2.5${\sim}$3.26 dB than those of the uncalibrated ones.

• 한국전기전자재료학회논문지
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• 제17권11호
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• pp.1234-1240
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• 2004

We studied on the electro-optic characteristics and dynamic stability according to an undesirably defined pretilt angle induced in high step coverage of pixel area for the Twisted Nematic (TN) / Fringe-Field Switching (FFS) mode. In case of the TN mode, LC directors twist reversely near the edges of thin-film-transistor and black matrix where the pretilt angle of the LC is not well defined. Therefore, the voltage-dependent dynamics of the LC in TN mode is unstable and shows the bad electro-optic characteristics. On the other hand, in case of the FFS mode, the LCs are twisted parallel to the bottom substrate by fringe electric field and the electro-optic characteristic is not influenced by the pretilt angle of the LC which is not well defined.

• 자동차안전학회지
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• 제13권4호
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• 한국의학물리학회지:의학물리
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• 제33권4호
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• pp.158-163
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• 2022

Purpose: We subjected scanning electron microscopic (SEM) images of the active layer of EBT3 film to texture analysis to determine the dose-response curve. Methods: Uncoated Gafchromic EBT3 films were prepared for direct surface SEM scanning. Absorbed doses of 0-20 Gy were delivered to the film's surface using a 6 MV TrueBeam STx photon beam. The film's surface was scanned using a SEM under 100× and 3,000× magnification. Four textural features (Homogeneity, Correlation, Contrast, and Energy) were calculated based on the gray level co-occurrence matrix (GLCM) using the SEM images corresponding to each dose. We used R-square to evaluate the linear relationship between delivered doses and textural features of the film's surface. Results: Correlation resulted in higher linearity and dose-response curve sensitivity than Homogeneity, Contrast, or Energy. The R-square value was 0.964 for correlation using 3,000× magnified SEM images with 9-pixel offsets. Dose verification was used to determine the difference between the prescribed and measured doses for 0, 5, 10, 15, and 20 Gy as 0.09, 1.96, -2.29, 0.17, and 0.08 Gy, respectively. Conclusions: Texture analysis can be used to accurately convert microscopic structural changes to the EBT3 film's surface into absorbed doses. Our proposed method is feasible and may improve the accuracy of film dosimetry used to protect patients from excess radiation exposure.

• Journal of the Optical Society of Korea
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• 제18권4호
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.