• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.8
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• pp.1176-1189
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• 1993

This paper presents the Multiple Keyword Retrieval Method under the Object-Oriented Multimedia Database Model. The multiple keyword registration and retrieval algorithms are developed to reduce the partial matching problem in multimedia data retrieval. For this, proper storage structures of the lookup tables are designed. And also, in order to maintain the constant retrieval time, media data files are organized with B+ tree structure.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.120-131
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• 1997

This paper prsents a new method that automatically recognizes the dimension lines (consisting of shape lines, tail lines and extension lines) from the mechanical drawings. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then the object lines and interpretation lines are vectorized by using several techniques such as thinning, line-vectorization, and vector-clustering. Finally, after recognizing arrowheads by using pattern matching, we recognize dimension lines from interpretation lines by using arrohead's directional vector and centroid. By using the methods of geometric modeling and mathematical operation, the proposed method readility recognizes the dimension lines from complex drawings. Experimental resuls are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.257-260
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• 2011

본 논문에서는 비디오 데이터로부터 물체의 초기 움직임 영역을 자동으로 검출하는 방법을 소개한다. 제안하는 시스템은 먼저 입력 영상을 받아들인 후 인접된 영상으로부터 일정 크기의 정방향의 블록 단위로 움직임을 나타내는 모션 벡터를 추출한다. 그리고 추출된 모션벡터를 아웃라이어를 제거하는 강건 예측 알고리즘에 적용하여 배경에 해당하는 모션벡터와 잡음 및 움직이는 물체에 해당하는 모션벡터를 구분한다. 그런 다음, 군집화 알고리즘을 적용하여 이동하는 물체를 나타내는 모션벡터를 군집화하고, 군집화된 모션벡터에 해당하는 영역의 크기가 일정 수치 값 이상일 때 움직이는 물체가 감지되었다고 판단한다. 본 논문의 실험에서는 제안된 물체의 움직임 감지 방법이 기존의 방법에 비해 성능이 보다 우수함을 보인다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.35-36
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• 2017

실시간 객체 인식은 카메라로부터 입력받은 영상 내에 존재하는 객체를 실시간으로 처리하는 기술로써 정확한 인식률과 빠른 인식 속도를 가져야 한다. 하지만 인식 속도가 보장되지 않으면 실시간으로 객체를 인식 할 수 없고 인식률이 보장되지 않으면 객체 인식을 통해 구현한 기능이 올바르게 동작하지 않을 수 도 있다. 따라서 본 논문에서는 실시간으로 객체를 인식하는 기술을 분류하고 연구 동향을 소개한다. 그리고 실시간 객체 인식을 위한 향후 연구 방향을 제시한다.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.10-17
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• 2018

Persistence Betty numbers, which are the rank of the persistent homology, are a generalized version of the size theory widely known as a descriptor for shape analysis. They show robustness to both perturbations of the topological space that represents the object, and perturbations of the function that measures the shape properties of the object. In this paper, we present a shape matching algorithm which is based on the use of persistence Betty numbers. Experimental tests are performed with Kimia dataset to show the effectiveness of the proposed method.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.142-145
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• 1997

This paper presents the development of depth extraction algorithm or the 3D Endoscopic Data using a stereo matching method and depth calculation. The purpose of other's algorithms is to reconstruct 3D object surface and make depth map, but a one of this paper is to measure exact depth information on the base of [cm] from camera to object. For this, we carried out camera calibration.

• ETRI Journal
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• v.37 no.3
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• pp.551-561
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• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.13-14
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• 2014

본 논문에서는 랜드마크를 활용한 카메라의 외곡에 대한 보정 기술을 제안한다. 이를 위해 OpenCV를 활용하여 랜드마크와 카메라로 부터 입력받은 영상의 매칭점을 비교하여 매칭 결과를 도출하며 매칭된 결과를 시스템 관리자에게 알려 줌으로써 카메라의 외곡을 확인 할 수 있다. 또한 제안한 방법을 활용하여 카메라의 외곡뿐만 아니라 외곡 각도 계산 까지 가능함에 따라 외부 환경으로 인한 카메라의 각도 변환에 대응 할 수 있으며 시스템 사용자의 편의성 및 비용 감소에도 도움이 될 것이다.

• Journal of International Society for Simulation Surgery
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• v.3 no.1
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• pp.16-21
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• 2016

Computed tomography (CT) can completely digitize the interior and the exterior of nearly any object without any destruction. Generally, the resolution for industrial CT is below a few microns. The industrial CT scanning, however, has a limitation because it requires long measuring and processing time. Whereas, 2D X-ray imaging is fast. In this paper, we propose a novel concept of 3D non-destructive inspection technique using the advantages of both micro-CT and dual X-ray images. After registering the master object’s CT data and the sample objects’ dual X-ray images, 3D non-destructive inspection is possible by analyzing the matching results. Calculation for the registration is accelerated by parallel computing using graphics processing unit (GPU).

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.