• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2558-2562
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• 1999

This paper proposes on the methods of noise removal and edge extraction which is done by eliminating the ambiguities of the image using normalization and minimizing the entropy. Pre-existing methods have their own peculiarities and limitations, such as gray level distributions change very slowly or two regions which having similar gray level distribution are touched. This affects on the post processing such as feature extraction, as a result, this leads to false-recognition or no-recognition. Therefore, this paper proposes on the methods which overcome these problems. Finally, the effectiveness of this paper is demonstrated by several experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.156-157
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• 2018

의료분야에서 원격판독은 보편화되어 있다. 하지만 이러한 원격판독에 필요한 전송과 관리 시스템은 부족하다. 본 논문에서는 가정용 카메라 모듈을 구성하고 이를 통해 모바일 애플리케이션으로 영상 스트리밍 및 사진 촬영을 하여 촬영된 사진을 치과로 전송하고 원격으로 검진할 수 있는 카메라 모듈 및 애플리케이션의 영상 전송을 위한 방법론을 제시한다. 안드로이드 애플리케이션과 카메라 모듈의 스트리밍 과정에는 여러 가지 문제가 발생한다. 모듈에서의 촬영 영상과 애플리케이션의 스트리밍 영상 간의 딜레이가 존재하는 것과 스트리밍 도중에 영상이 검은 화면으로 나왔다가 다시 돌아오거나 화절 저하 현상이 일어나는 것이다. 이러한 문제점들을 개선하고 최적화 할 수 있도록 한다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3675-3682
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• 1999

This paper proposes the method to extract face components without using the color information and the motion information in a gray image. A laplacian pyramid of the original image is built. Eye and nose candidates are extracted using only the gray information in a low resolution laplacian image and pairs are found that consist of two eye candidates and a nose one. At full resolution, horizontal and vortical edges are found in the regions of face components which are established using the candidates. Using those edge informations, face components are extracted. The experiments have been performed for images with various sizes and positions of face, and show very encouraging result.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.94-97
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• 2020

코로나 시대에 도래하며 비접촉 방식의 생체 징후에 대한 관심이 증가하고 있다. 본 연구는 비접촉식 측정 방식으로써 모바일 전면 카메라를 이용하여 심장박동, 심장 박동 변이율, 산소포화도, 호흡도, 스트레스 수치를 측정할 수 있는 효과적인 방법론을 제시하는 것이 목적이다. 모바일 전면부 카메라에서 실시간으로 안면 영상을 추출하기 위하여 Blaze Face를 이용하였으며, 안면 영상의 특징점인 눈, 코, 입, 귀의 위치를 이용하여 이마 부분의 관심 영역을 지정하였다. 관심 영역에서 색상 성분을 R, G, B로 분리하여 시간 축으로 정렬 후 fourier transform을 진행한 후 각각의 성분들을 측정하고자 하는 생체 징후에 맞게 Filter 처리함으로써 생체 징후를 측정하였다. 안면 영상을 이용한 생체 징후 측정 결과를 검증에 활용하기 위하여 실측 기기인 mCube-Healthcare device를 이용하였으며, 분석 결과 모바일에서 안면 영상을 통해 심장박동, 삼장 박동 변이율, 산소포화도, 호흡도, 스트레스 수치의 다섯 가지 생체 징후를 추출할 수 있는 가능성을 확인하였다.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1771-1777
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• 2023

With the advancements of deep learning, many semantic segmentation-based methods for land cover classification have been proposed. However, existing deep learning-based models only use image information and cannot guarantee spatiotemporal consistency. In this study, we propose a land cover classification model using geographical coordinates. First, the coordinate features are extracted through the Coordinate Hash Encoder, which is an extension of the Multi-resolution Hash Encoder, an implicit neural representation technique, to the longitude-latitude coordinate system. Next, we propose an architecture that combines the extracted coordinate features with different levels of U-net decoder. Experimental results show that the proposed method improves the mean intersection over union by about 32% and improves the spatiotemporal consistency.

• Archives of design research
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• v.18 no.2 s.60
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• pp.101-110
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• 2005

Simulacre is one of the major topics in the Western philosophy since Plato. Since the 20th century, the Western philosophy is based on rationalism toward 'absolute truth' founded on Platonic Ideas. The concept of Simulacre is ignored and rejected until the modern days. However, Simulacre is gaining its attention at this time of image. and the time of Simulacre. The concept of postmodern Simulacre started from Walter Benjamin is developed by Gnther Anders, Jacques Derrida, Gilles Deleuze, and Jean Baudrillard. This study, based on the Jean Baudrillard's concept of Simulacre, examines today's Simulacre phenomena and analyzes the cinematic works of Oshii Mamoru who displays the concept of Simulacre in his films. Analyzing and evaluating his recent visual works based on Simulacre theory with such superficial methods as advanced special visual effects is a mistake that demeans Simulation? (Matrix). Today, Simulacre phenomena are scattered all over our life. The search of its substance and the analysis of his artworks will be a foundation that makes a new alternative suggestion.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.5-18
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• 2013

This study analyzed the effect by comparing it with 2D game using playtest experimental treatment methodology to verify the video effect, materiality and fatigue effect of 3D video game. First, for the hypothesis to verify the difference of video experience of users for 3D and 2D games, visual clarity was rejected, but materiality, tangibility and presence hypotheses were all accepted. Second, it was shown that there was no difference in eye fatigue and physical fatigue in 3D and 2D games. It was different from results of existing research which claimed that fatigue occurred due to video distortion occurring in 3D video and fatigue inducing factors. Third, the results of measurement of changes in brain wave occurring in the course of playing 3D and 2D games showed that there was no difference in average amplitude of EEG alpha wave, but EEG beta wave occurred in higher amplitude. This study proved the cerebral physiological change and difference in the process of experience to use 3D video game by complementing the methodology in measurement in EEG brain wave in the traditional experimental method.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.47-54
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• 2017

Recently, there are many studies related aerial mapping project and 3 dimensional shape and model reconstruction using UAV(unmanned aerial vehicle) system and images. In this study, we create 3D reconstruction point data using image matching technology of the UAV overlap images, detect shape change of structure and perform accuracy assessment of area($m^2$) and volume($m^3$) value. First, we build the test structure model data and capturing its images of shape change Before and After. Second, for post-processing the Before dataset is convert the form of raster format image to ensure the compare with all 3D point clouds of the After dataset. The result shows high accuracy in the shape change of more than 30 centimeters, but less is still it becomes difficult to apply because of image matching technology has its own limits. But proposed methodology seems very useful to detect illegal any structures and the quantitative analysis of the structure's a certain amount of damage and management.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1698-1706
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• 1997

In this paper, we envisioned a multimedia object recognition system processing and combinig information from all available sources, such as 2-D, 3-D, color and sound data. Out of the overall system, we proposed 3-D information extraction and object recognition methods. Firstly, surfaces are classified by z-gradient from the range data, surface features are extracted using the intersection of normal vectors. Also feature relationship such as intersection angle and distance is established between the surfaces. Secondly, recognition is accomplished by matching process which is improtant step in the image understanding systems. Matching process is very improtant procedures because of more general and more efficient method is needed in the field of multimedia sytem. Therefore, we focused the proposal of matching process and in this article, first of all, we deal with the matching process of the 3-D object. Similarity measures are calculated.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.151-156
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• 2018

In this paper, a method to classify objects in outdoor CCTV images using Convolutional Neural Network(CNN) and background subtraction is proposed. Object candidates are extracted using background subtraction and they are classified with CNN to detect objects in the image. At the end, computation complexity is highly reduced in comparison to other object detection algorithms. A database is constructed by filming alleys and playgrounds, places where crime occurs mainly. In experiments, different image sizes and experimental settings are tested to construct a best classifier detecting person. And the final classification accuracy became 80% for same camera data and 67.5% for a different camera.