• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.986-987
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• 2023

본 논문은 신경근육질환 환자의 이동 문제를 해결하고, 기존 전동킥보드 시스템의 한계와 문제점도 해결하는 '신경근육질환 환자를 위한 전동킥보드 안전 환경 시스템'을 제안한다. 주요 특징은 다음과 같다. 첫째, 헬멧 착용 검사를 통과해야만전동킥보드를 이용할 수 있다. 휴대폰 전면 카메라를 통해 사용자의 모습을 촬영하면 딥러닝 모델을 통해 헬멧 착용 여부를 판단한다. 둘째, 주행 금지구역에서는 이용자 추적 모드를 활성화하여 OpenCV를 통해 이용자를 검출및 추적하고이에 따라 모터 PWM을 조절해서 방향 및 속력을 조절함으로써 이용자를 추적한다. 셋째, 헬멧 내 자이로 센서와 쇼크 센서를 통해 주행 사고를 감지하고 SMS를 이용해 해당 보호자에게 자동으로 사고 정보를 전달한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1035-1036
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• 2023

본 논문은 저시력자를 위한 체외진단 의료기기 결과 판독 시스템을 제안한다. 이 시스템은 YOLOv8n 객체 탐지 모델을 기반으로 하며, 라즈베리파이4B+에서 홈 디바이스 형태로 구현하였다. 사용자는 음성 및 물리 버튼을 통해 명령을 입력하고, 동작 감지를 통해 자동으로 체외진단 의료기기를 촬영하여 학습된 모델로 결과를 판독하고 해당 결과를 사용자에게 출력한다. 또한, 판독 결과물과 함께 검사 일시 및 의료기기 종류를 데이터베이스에 저장하여 사용자에게 보다 높은 편의성을 제공한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.411-412
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• 2024

본 논문에서는 인공위성 이미지 비교 알고리즘을 설계하여 국제원자력기구(IAEA)와의 안전조치협정 추가의정서에 따른 원자력 시설 부지 정보의 변동 사항을 검출하는 시험을 수행하였다. 구글 어스에서 특정 장소에 대해 촬영 시간이 다른 인공위성 이미지를 얻어 시험 데이터로 사용하고 본 논문에서 개발한 5단계 이미지 비교 알고리즘을 구동한 결과 추가되거나 사라진 건물을 추적할 수 있었다. 향후 알고리즘 성능에 중요한 역할을 하는 검출 조정값(역치) 자동 도출 기능 및 이미지 전처리 프로세스를 개선한다면 대량 이미지 분석이 필요한 업무에 활용할 수 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.319-322
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• 2007

본 논문에서는 영상 감시 등의 응용을 위해 영상에서 자동으로 사람 수를 측정하는 군중 수 측정 방법을 제안한다. 제안한 방법에서는 전처리 과정으로 전경영상과 경계영상을 검출하여 객체의 픽셀 크기 히스토그램과 경계 방향 히스토그램을 특징으로 이용하고 카메라 투영행렬을 통해 픽셀 크기와 경계 방향에 대한 특징 정규화를 수행한다. 실제 사람 수와 얻어진 특징 히스토그램 간의 선형성은 사상 함수의 구성에 적용되며, 훈련 데이터를 통해 얻어진 사상 함수는 사람 수 측정에 이용되었다. 제안한 방법의 성능은 건물 내에서 촬영된 영상에 대한 실험 결과로 나타났으며 이 방법이 영상 감시 분야에 다양하게 적용될 수 있음이 확인되었다.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.12 no.1
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• pp.10-15
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• 2009

Purpose: The manner of rectal bleeding of auto-amputated polyps (AP) is similar to juvenile polyps (JP) or Meckel's diverticula (MD). We conducted this study to characterize the clinical spectrum of AP. Methods: Fourteen patients were enrolled this study who were diagnosed AP due to painless rectal bleeding. The clinical data of AP was assessed and then compared with the clinical data of JP and MD retrospectively. Results: The prevalence of AP was 10.4% (14/135) and high in younger patients compared with that of JP (p=0.042 below 2 years). Whereas JP was more common in patients aged 2 to 5 years (p=0.005). Male was predominant in AP (p=0.008 AP vs JP). The manner of rectal bleeding in AP group was sudden and transient. There was no significant difference in time interval between onset of rectal bleeding and diagnosis between the 3 groups. However AP was diagnosed in 9 patients (64.3%) within 7 days after onset of rectal bleeding, but JP was diagnosed in 5 patients (4.1%) in the same period (p<0.001). All of AP were located in the rectum and the sigmoid colon. The mean hemoglobin was 11.3${\pm}$1.5 g/dL in AP, 11.8${\pm}$1.3 g/dL in JP, and 8.4${\pm}$1.2 g/dL in MD (p<0.001, only significant in MD). Conclusion: AP may be considered in male older than 1 year with transient and sudden onset or increase of painless rectal bleeding without drop of hemoglobin level.

• Progress in Medical Physics
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• v.26 no.1
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Investigative Magnetic Resonance Imaging
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• v.17 no.3
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• pp.200-206
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• 2013

Purpose : To assess the effect of applying an automated heart model based measurements of left ventricle (LV) and compare with manual and semi-automated measurements at Cardiovascular MR Imaging. Materials and Methods: Sixty-two patients who underwent cardiac 1.5T MR imaging were included. Steady state free precession cine images of 20 phases per cardiac cycle were obtained in short axis views and both 2-chamber and 4-chamber views. Epicardial and endocardial contours were drawn in manual, automated, and semi-automated ways. Based on these acquired contour sets, the end-diastolic (ED) and end-systolic (ES) volumes, ejection fraction (EF), systolic volume (SV) and LV mass were calculated and compared. Results: In EDV and ESV, the differences among three measurement methods were not statistically significant (P = .399 and .145, respectively). However, in EF, SV, and LV mass, the differences were statistically significant (P=.001, <001, <001, respectively) and the measured value from automated method tend to be consistently higher than the values from other two methods. Conclusion: An automatic heart model-based method grossly overestimate EF, SV and LV mass compared with manual or semi-automated methods. Even though the method saves a considerable amount of efforts, further manual adjustment should be considered in critical clinical cases.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.861-869
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• 2020

We introduce the application that automatically makes several images stored in user's device into one video by using the different climax patterns appearing for each film genre. For the classification of the genre characteristics of movies, a climax pattern model style was created by analyzing the genre of domestic movie drama, action, horror and foreign movie drama, action, and horror. The climax pattern was characterized by the change in shot size, the length of the shot, and the frequency of insert use in a specific scene part of the movie, and the result was visualized. The model visualized by genre developed as a template using Firebase DB. Images stored in the user's device were selected and matched with the climax pattern model developed as a template for each genre. Although it is a short video, it is a feature of the proposed application that it can create an emotional story video that reflects the characteristics of the genre. Recently, platform operators such as YouTube and Naver are upgrading applications that automatically generate video using a picture or video taken by the user directly with a smartphone. However, applications that have genre characteristics like movies or include video-generation technology to show stories are still insufficient. It is predicted that the proposed automatic video editing has the potential to develop into a video editing application capable of transmitting emotions.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.205-214
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• 2014

Minimization of visual fatigue is important for production of high quality stereoscopic 3D contents. Vertical disparity of stereo images occurred during contents production is considered as the main factor of visual fatigue. To ensure correct stereoscopy vertical disparity needs to be eliminated. In this paper, a method for automated image alignment was proposed for Stereoscopic 3D contents generation and post-processing steps. The proposed method consists of two parts: rectification for image alignment and camera motion detection. The proposed method showed that its rectification performance was the most superior among the existing methods tested and that camera motion detection had a success rate of 98.35%. Through these evaluations, we confirmed that the proposed method can be effectively applied to 3D contents production.