• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.268-270
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• 2003

국내에서의 의료영상에 관한 관심도가 높아짐에 따라 Visible Korean Human Project가 시작되었다. 이를 통해 얻어진 해부영상들의 다양한 응용을 위해 분할작업은 필수적 단계로 이를 분할하기 위한 도구가 필요하다. 그러나 분할해야할 기관들의 종류가 많고 그 특성이 다양해서 기존의 분할도구로 적용하기에 많은 문제점이 나타나 새로운 분할도구개발의 필요성이 나타났다. 새로운 분할도구에서는 각 기관의 특성 에 알맞은 다양한 방법의 분할 방범을 제공하여 분할방법에 따라 다른 분할결과를 통합적으로 표현하여 보다 용이한 처리를 가능하도록 설계되었다. 구현된 분할 도구는 반자동 분할 방법과 슬라이스간 전달 방법을 사용하여 보다 적은 사용자의 입력으로도 빠른 시간에 많은 양의 데이터를 분할 할 수 있도록 자동화 설계되었으며, 자동적으로 분할된 결과가 사용자의 의도와 다른 경우 설계 편집할 수 있는 기능도 제공하도록 구현했다. 구현된 분할도구를 통해 Visible Korean Human Dataset의 분할 실험을 했으며 기존의 분할 도구에 비해 이르고 정확한 결과를 얻어 낼 수 있었다.

• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.35-53
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• 2012

컴퓨터 그래픽스 및 관련 연구 분야는 지난 30년간 눈부신 발전을 거듭해왔다. 모델링, 렌더링, 애니메이션 등 시각적 표현력을 확보하는 것을 목표로 출발한 컴퓨터 그래픽스 연구는 점차 그 범위를 확대해서 영상처리, 자연현상 시뮬레이션, 가상현실, 의료 영상, 인간-컴퓨터 상호작용, 실시간 시뮬레이션, 영화 특수 효과 등 다양한 연구 및 응용분야를 파생 시키며 점차 복잡한 지형도를 그려가고 있다. 이 글은 전체 2편의 연속 논문 중에서 2부에 해당하며, 컴퓨터 그래픽스의 응용 분야 중에서 국내 연구가 활발한 옷 시뮬레이션, 비사실적 렌더링, 음향 시뮬레이션, 가상현실, 증강현실의 최근 연구 동향을 분석하고 정리한다.

• Information and Communications Magazine
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• v.32 no.2
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• pp.34-40
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• 2015

본고에서는 실감 영상회의와 몰입형 텔레프레즌스의 수준을 넘어 물리적으로 떨어져 있는 원격 다지점(Multi-point)의 공간을 초실감적으로 가상 연결할 수 있는 스마트월(Smart-Wall) 기술 개념에 대해 살펴본다. 여기서 초실감이란 UHD-4K/8K급 또는3차원 이상의 초실감 영상기술과 사람의 모든 발성대역을 재현할 수 있는 슈퍼와이드밴드 기반 초실감 음성처리 및 동급 수준의 미디어 통신 기술을 적용한 사용자의 서비스 인지품질 수준을 의미한다. 이러한 초실감 수준의 현장감과 몰입감을 멀리 떨어진 1:1 또는 다지점 간 사용자들에게 안정적인 고품질로 제공할 수 있는 스마트월 핵심기술의 확보는 초실감 스마트워크 뿐 아니라 동급의 원격교육, 원격의료 서비스와 제품에 시급히 요구되고 있다. 원격 다지점 공간을 초실감으로 가상연결 하는 스마트월 기술은 사용자가 마치 현장에 있는 것처럼 실감성을 제공할 수 있는 핵심기술로써, 실감 ICT 올림픽에 접목이 되면 현장에 참석한 것 이상의 실감있는 대면 대화, 인터뷰 및 협업작업이 가능한 서비스를 제공할 수 있어 실감 ICT 올림픽에서 가장 인기있는 세계 최초의 기가미디어급 미래서비스가 될 것으로 예상한다.

• Convergence Security Journal
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• v.19 no.5
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• pp.75-84
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• 2019

Recently, the value of video as an important data of medical information technology is increasing due to the feature of rich clinical information. On the other hand, video is also required to be de-identified as a medical image, but the existing methods are mainly specialized in the stereotyped data and still images, which makes it difficult to apply the existing methods to the video data. In this paper, we propose an automated system to index candidate elements of personal identification information on a frame basis to solve this problem. The proposed system performs indexing process using text and person detection after preprocessing by scene segmentation and color knowledge based method. The generated index information is provided as metadata according to the purpose of use. In order to verify the effectiveness of the proposed system, the indexing speed was measured using prototype implementation and real surgical video. As a result, the work speed was more than twice as fast as the playing time of the input video, and it was confirmed that the decision making was possible through the case of the production of surgical education contents.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.131-134
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• 2008

한의학의 대중화와 세계화를 위해서는 타 의학과의 차별화와 진단의 객관성 확보가 매우 중요하며 이를 위해서는 한의학의 독창적인 의료체계인 사상의학을 통해 차별화를 이루고 또한 객관성 확보를 위해 IT 공학기술과 연계하여 진단기술을 개발한다면 효율적일 것으로 예상한다. 본 논문에서는 사상의학의 체질 분류를 목적으로 하여 체질 분류법 중 용모사기론을 기반으로 한 안면 영상을 통한 사상체질 분류시스템을 개발하기위해 20대 여성을 대상으로 안면 영상을 수집하고 피실험자에 대한 체질분류 작업을 진행하여 안면 요소와 체질 간의 상관관계를 분석하여 체질별 차이를 나타내는 항목을 설정하고 이에 대한 분석을 실험을 통해 수행하고자 한다.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.391-400
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• 2004

Within multimodal medical image registration techniques, which correlate different images and Provide integrated information, surface registration methods generally minimize the surface distance between two modalities. However, the features of two modalities acquired from one subject are similar. So, it can improve the accuracy of registration result to match two images based on optimization of both surface distance and shape feature. This research proposes a registration method which optimizes surface distance and surface curvature of two brain modalities. The registration process has two steps. First, surface information is extracted from the reference images and the test images. Next, the optimization process is performed. In the former step, the surface boundaries of regions of interest are extracted from the two modalities. And for the boundary of reference volume image, distance map and curvature map are generated. In the optimization step, a transformation minimizing both surface distance and surface curvature difference is determined by a cost function referring to the distance map and curvature map. The applying of the result transformation makes test volume be registered to reference volume. The suggested cost function makes possible a more robust and accurate registration result than that of the cost function using the surface distance only. Also, this research provides an efficient means for image analysis through volume visualization of the registration result.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.407-412
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• 2007

The performance of ultrasonic testing systems for industrial or medical purpose largely depends on the performance of ultrasonic transducers. Generally, the information about an ultrasonic transducer performance characteristics are expressed by the ultrasonic R/F signal back from a reflector and its frequency characteristics in the data sheet provided by manufacturers. In case of focused ultrasonic transducers, the two pieces of information can, however, hardly assure that the focused ultrasonic transducer would produce well-focused C-scan images. Therefore, we propose the measured size of focal spot and the reconstructed shape of effective focal zone in the focused sound field as novel measures for the performance evaluation of the focused ultrasonic transducers. The process of getting the both measures of the transducers is conducted by the implemented software including sound field scanning and virtual 3D reconstruction functions which requires the echo of a point reflector. The proposed method could, otherwise impossible in the existing method, effectively and simply distinguish superior ones among many transducers made in the same specification and be also used to detect the performance degradation due to the aging of the transducers. Eventually, the quality of performance of the ultrasonic testing systems for industrial or medical purpose is secured.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.71-80
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• 2007

In this paper, We propose face type classification, tongue region extraction and tongue color analysis method for Oriental medicine diagnosis system to supply web based medical treatment information. This presents to construct system that takes super aging society and uses ocular inspection and longue diagnosis in web-based to embody this by an IT Technology as generalization and popularization of medical benefit are social requirement and supplies medical treatment information. Place that reflect living body signal of human body ordinarily and appear becomes iris or tongue, five sensory organs etc. This paper proposes classification of face type, extraction of five sensory organs for observing a person's shape and color among diseases diagnosis based on home health care that propose to develop and region extraction and color analysis etc, of tongue which intensively represents the bio-signals of human-beings. Finally, the effectiveness of this paper is verified by several experiments.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.158-165
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• 2019

Although evaluation of writing disabilities identification and timely intervention are required, clinicians adopt a manual scoring method and there is a possibility of error due to subjective evaluation. In this study, the size ratio and position of letters are digitized and quantified through image processing of offline handwritten characters. We tried to evaluate objectively and accurately the performance of writing through comparison with existing methods. From November 12th to 16th, 2018, 20 adults without neurological injury were selected. They used a pencil to follow the 10 words, 2 sentence stimuli after keeping the usual habit, and we collected the writing test data. The results showed that the height of the word was 1.2 times larger than the width and it tilted to the lower left. The spacing interval was 9mm on average. In the Paired T test, a high correlation was showed between our system and existing methods in the word and sentence 2. This demonstrated the possibility as a testing tool. This study evaluated objectively and precisely writing performance of offline handwritten characters through image processing and provided preliminary data for performance standards. In the future, it can be suggested as a basic data on writing diagnosis of various ages.