• Annual Conference of KIPS
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• 2014.11a
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• pp.1199-1202
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• 2014

본 논문은 차량에 설치된 블랙박스 영상으로부터 도로 노면에 표시된 방향지시 기호를 효율적으로 검출하는 방안을 제안한다. 차량 내부에 설치된 블랙박스 영상은 카메라의 원근 효과로 인해 방향지시 기호 영역을 올바르게 검출하지 못하는 문제점이 존재한다. 따라서 제안한 연구에서는 원근 효과를 가진 입력 영상에서 역원근 변환 방법을 통해 원근 효과를 제거한 실세계 좌표로 맵핑한 평면 영상에서 방향지시 기호 영역을 신경망 검출기를 통해 검출한다. 입력 영상에서 역 원근 변환은 높은 계산량으로 인해 실시간 처리가 어려운 점이 존재한다. 이를 보완하기 위해 제안한 방안에서는 입력 영역의 도로노면 방향지시 기호 영역의 특징을 분석하여 도로노면 기호가 포함된 후보 ROI영역을 정의하고 후보 ROI 영역의 Gray 색상에서 역원근 변환을 수행한다. 제안한 방안을 도로노면 방향지시 기호 검출 및 인식 연구에 적용한 결과, 약 87% 이상 비교적 정확히 검출율을 제시하였으며, 다양한 도로 환경에서도 높은 검출율을 제시하였다. 따라서 제안한 방안을 운전자의 안전운전지원시스템에 적용함으로써 보다 정확한 도로정보 제공시스템 적용이 가능함을 알 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.59-62
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• 2018

In this paper, we propose a contrast enhancement algorithm using guided image filter (GIF). The GIF is used to divide an HDR image into a base layer and a detail layer. The energy scale of base layer determinate the darkness and brightness of the image. However, the detail information in the base layer is difficult to be displayed because of the high brightness and clusters of low brightness. We propose a contrast enhancement method by adjusting the gray level of base layer by subtracting the mean value of itself. It is combined with the detail layer to preserve the detail information. Experiment results show that the proposed algorithm has better performance in detail preservation and contrast enhancement.

• The Korean Journal of Nuclear Medicine
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• v.38 no.1
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• pp.30-40
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• 2004

Purpose: The aims of this study were to find brain regions in which gray matter volume was reduced and to show the capability of voxel-based morphometry (VBM) analysis for lateralizing epileptogenic zones in medial temporal lobe epilepsy (mTLE). The findings were compared with fluorodeoxyglucose positron omission tomography (FDG PET). Materials and Methods: MR T1-weighted images of 12 left mTLE and 11 right mTLE patients were compared with those of 37 normal controls. Images were transformed to standard MNI space and averaged in order to create study-specific brain template. Each image was normalized to this local template and brain tissues were segmented. Modulation VBM analysis was performed in order to observe gray matter volume change. Gray matter was smoothed with a Gaussian kernel. After these preprocessing, statistical analysis was peformed using statistical parametric mapping software (SPM99). FDG PET images were compared with those of 22 normal controls using SPM. Results: Gray matter volume was significantly reduced in the left amygdala and hippocampus in left mTLE. In addition, volume of cerebellum, anterior cingulate, and fusiform gyrus in both sides and left insula was reduced. In right mTLE, volume was reduced significantly in right hippocampus. In contrast, FDG uptake was decreased in broad areas of left or right temporal lobes in left TLE and right TLE, respectively. Conclusions: Gray matter loss was found in the ipsilateral hippocampus by modulation VBM analysis in medial temporal lobe epilepsy. This VBM analysis might be useful in lateralizing the epileptogenic zones in medial temporal lobe epilepsy, while SPM analysis of FDG PET disclosed hypometabolic epileptogenic zones.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.545-559
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• 2020

In this paper, we propose a content creation framework that enables users without programming experience to easily create interactive media content that responds to user gestures. In the proposed framework, users define the gestures they use and the media effects that respond to them by numbers, and link them in a text-based configuration file. In the proposed framework, the interactive media content that responds to the user's gesture is linked with the dynamic projection mapping module to track the user's location and project the media effects onto the user. To reduce the processing speed and memory burden of the gesture recognition, the user's movement is expressed as a gray scale motion history image. We designed a convolutional neural network model for gesture recognition using motion history images as input data. The number of network layers and hyperparameters of the convolutional neural network model were determined through experiments that recognize five gestures, and applied to the proposed framework. In the gesture recognition experiment, we obtained a recognition accuracy of 97.96% and a processing speed of 12.04 FPS. In the experiment connected with the three media effects, we confirmed that the intended media effect was appropriately displayed in real-time according to the user's gesture.

• Korean Journal of Biological Psychiatry
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• v.19 no.2
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• pp.77-83
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• 2012

Objectives : Although there have been studies that examine sex differences of the brain structures using magnetic resonance imaging, studies that specifically investigate cerebellar structural differences between men and women are scarce. The purpose of current study was to examine sex differences in structures of the cerebellum using cerebellar template and cerebellum analysis methods. Methods : Sixteen men and twenty women were included in the study. A MATLAB based program (MathWorks, Natick, MA, USA), Statistical Parametric Mapping 5 (SPM5) using the spatially unbiased infra-tentorial atlas template (SUIT) as the cerebellum template, was used to analyze the brain imaging data. Results : There was no significant difference in age between men (mean age=28.1) and women (mean age=27.2). Men showed higher gray matter density than women in two left cerebellar areas including the clusters in the lobules IV and V (a cluster located across the lobules IV and V), and the lobule VIIIb (lobules IV and V, t=4.75, p<0.001 ; lobule VIIIb, t=3.08, p=0.004). Conclusions : The current study found differences in cerebellar gray matter density between men and women. The current study holds its significance for applying the template specifically developed for the analysis of cerebellum.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1938-1962
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• 2015

Security of information during transmission is a major issue in this modern era. All of the communicating bodies want confidentiality, integrity, and authenticity of their secret information. Researchers have presented various schemes to cope with these Internet security issues. In this context, both steganography and cryptography can be used effectively. However, major limitation in the existing steganographic methods is the low-quality output stego images, which consequently results in the lack of security. To cope with these issues, we present an efficient method for RGB images based on gray level modification (GLM) and multi-level encryption (MLE). The secret key and secret data is encrypted using MLE algorithm before mapping it to the grey-levels of the cover image. Then, a transposition function is applied on cover image prior to data hiding. The usage of transpose, secret key, MLE, and GLM adds four different levels of security to the proposed algorithm, making it very difficult for a malicious user to extract the original secret information. The proposed method is evaluated both quantitatively and qualitatively. The experimental results, compared with several state-of-the-art algorithms, show that the proposed algorithm not only enhances the quality of stego images but also provides multiple levels of security, which can significantly misguide image steganalysis and makes the attack on this algorithm more challenging.

• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.623-629
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• 2003

In this paper, we have proposed a full phase encryption scheme based on phase-encoded XOR operation. The proposed scheme encrypts a gray-level image by slicing an original image and combining with XORed images which resulted from phase-encoded XOR operations between sliced images and phase-encoded binary random images. Then we produce an encrypted image by combining only XORed images and a key image by only phase-encoded binary random images. The encrypted image and key image are converted into encrypted data and key data by a phase-encoding method. The merits are that the proposed encryption scheme can basically fulfill a high-level encryption using a full phase encryption scheme which has nonlinear and invisible characteristics. The scheme also improves security by encrypting the phase information before full phase encryption. The decryption system based on the principle of interference between a reference wave and a direct pixel-to-pixel mapping image of encrypted data with key data can be simply implemented using a phase-visualization system. Simulation results indicate that our proposed encryption scheme is effective and simple for a gray-scale image and optical decryption system.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1131-1141
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• 2023

Objective: Cortical iron deposition has recently been shown to occur in Alzheimer's disease (AD). In this study, we aimed to evaluate how cortical gray matter iron, measured using quantitative susceptibility mapping (QSM), differs in the clinical cognitive impairment spectrum. Materials and Methods: This retrospective study evaluated 73 participants (mean age ± standard deviation, 66.7 ± 7.6 years; 52 females and 21 males) with normal cognition (NC), 158 patients with mild cognitive impairment (MCI), and 48 patients with AD dementia. The participants underwent brain magnetic resonance imaging using a three-dimensional multi-dynamic multi-echo sequence on a 3-T scanner. We employed a deep neural network (QSMnet+) and used automatic segmentation software based on FreeSurfer v6.0 to extract anatomical labels and volumes of interest in the cortex. We used analysis of covariance to investigate the differences in susceptibility among the clinical diagnostic groups in each brain region. Multivariable linear regression analysis was performed to study the association between susceptibility values and cognitive scores including the Mini-Mental State Examination (MMSE). Results: Among the three groups, the frontal (P < 0.001), temporal (P = 0.004), parietal (P = 0.001), occipital (P < 0.001), and cingulate cortices (P < 0.001) showed a higher mean susceptibility in patients with MCI and AD than in NC subjects. In the combined MCI and AD group, the mean susceptibility in the cingulate cortex (β = -216.21, P = 0.019) and insular cortex (β = -276.65, P = 0.001) were significant independent predictors of MMSE scores after correcting for age, sex, education, regional volume, and APOE4 carrier status. Conclusion: Iron deposition in the cortex, as measured by QSMnet+, was higher in patients with AD and MCI than in NC participants. Iron deposition in the cingulate and insular cortices may be an early imaging marker of cognitive impairment related neurodegeneration.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.35-39
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• 2009

Purpose: Diagnostic and functional imaging softwares in Nuclear Medicine have been developed significantly. But, there are some limitations which like take a lot of time. In this article, we introduced that the basic concept of macro to help understanding macro and its application to Brain SPECT processing. We adopted macro software to SPM processing and PACS verify processing of Brain SPECT processing. Materials and Methods: In Brain SPECT, we choose SPM processing and two PACS works which have large portion of a work. SPM is the software package to analyze neuroimaging data. And purpose of SPM is quantitative analysis between groups. Results are made by complicated process such as realignment, normalization, smoothing and mapping. We made this process to be more simple by using macro program. After sending image to PACS, we directly input coordinates of mouse using simple macro program for processes of color mapping, adjustment of gray scale, copy, cut and match. So we compared time for making result by hand with making result by macro program. Finally, we got results by applying times to number of studies in 2007. Results: In 2007, the number of SPM studies were 115 and the number of PACS studies were 834 according to Diamox study. It was taken 10 to 15 minutes for SPM work by hand according to expertness and 5 minutes and a half was uniformly needed using Macro. After applying needed time to the number of studies, we calculated an average time per a year. When using SPM work by hand according to expertness, 1150 to 1725 minutes (19 to 29 hours) were needed and 632 seconds (11 hours) were needed for using Macro. When using PACS work by hand, 2 to 3 minutes were needed and for using Macro, 45 seconds were needed. After applying theses time to the number of studies, when working by hand, 1668 to 2502 minutes (28 to 42 hours) were needed and for using Macro, 625 minutes (10 hours) were needed. Following by these results, it was shown that 1043 to 1877 (17 to 31 hours were saved. Therefore, we could save 45 to 63% for SPM, 62 to 75% for PACS work and 55 to 70% for total brain SPECT processing in 2007. Conclusions: On the basis of the number of studies, there was significant time saved when we applied Macro to brain SPECT processing and also it was shown that even though work is taken a little time, there is a possibility to save lots of time according to the number of studies. It gives time on technologist's side which makes radiological technologist more concentrate for patients and reduce probability of mistake. Appling Macro to brain SPECT processing helps for both of radiological technologists and patients and contribute to improve quality of hospital service.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.