• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.535-537
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• 2000

인체 장기의 내부 벽면을 관찰하기 위하여 사용된 내시경 검사 기법은 내시경을 삽입하고, 질병 부위를 찾는 과정에서 환자에게 고통을 유발시키고, 정확한 진단을 내리기 위해서는 검사자의 오랜 경험과 숙달을 필요로 한다. 그러므로 각종 의료 영상을 기반으로 한 가상 내시경 시스템에 대한 연구와 개발이 요구된다. 본 논문에서는 초음파 영상을 기반으로 하여 병변 부위의 3차원 영상을 생성하고, 탐색하는 시스템을 제안한다. 우선 획득된 초음파 영상으로부터 장기에 대한 윤곽선 정보를 얻기 위하여, 초음파 영상에 대한 전처리 작업과 분할 작업을 수행하였고, 추출된 윤곽선 정보를 기반으로 3차원 표면 모델을 생성하였다. 3차원 표면 모델은 VRML 2.0 형식의 3차원 객체로 자동 변환되어 일반 VRML Plug-in viewer 및 자바 제어 모듈을 이용하여 3차원 장기 모델에 대한 탐색을 가능하도록 하였다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.75-82
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• 2010

The paper proposed CBIRS/EFI with contents based search technique using edge feature information of the object from image information of the object which is uncertain. In order to search specially efficiently case of partial image information of the object, we used the search technique which extracts outline information and color information in feature information of object. In order to experiment this, we extracted side edge feature information of the vehicle for feature information of the object after capture the car image of the underground garage. This is the system which applies a contents base search by the result which analyzes the image which extracts a feature, an original image to search and a last similar measurement result. This system compared in FE-CBIRS systems which are an existing feature extraction contents base image retrieval system and the function which improves the accuracy and an effectiveness of search rate was complemented. The performance appraisal of CBIRS/EFI systems applied edge extraction feature information and color information of the cars. And we compared a color feature search time, a shape characteristic search time and a search rate from the process which searches area feature information. We extracted the case 91.84% of car edge feature extraction rate. And a average search time of CBIRS/EFI is showing a difference of average 0.4-0.9 seconds than FE-CBIRS from vehicle. color search time, shape characteristic search time and similar search time. So, it was proven with the fact that is excellent.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.109-116
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• 2003

In this paper, a CORBA-based collaborative medical image analysis and visualization system, which provides high accessibility and usability of the system for the users on distributed environment is introduced. The system allows us to manage datasets and manipulates medical images such as segmentation and volume visualization of computed geometry from biomedical images in distributed environments. Using Bayesian classification technique and an active contour model the system provides classification results of medical images or boundary information of specific tissue. Based on such information, the system can create real time 3D volume model from medical imagery. Moreover, the developed system supports collaborative work among multiple users using broadcasting and synchronization mechanisms. Since the system is developed using Java and CORBA, which provide distributed programming, the remote clients can access server objects via method invocation, without knowing where the distributed objects reside or what operating system it executes on.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.529-536
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• 2015

When rendering both three-dimensional objects and photo images together, the non-photorealistic rendering results are in visual discord since the two contents have their own independent color distributions. This paper proposes a non-photorealistic rendering technique which renders both three-dimensional objects and photo images such as cartoons and sketches. The proposed technique computes the color distribution property of the photo images and reduces the number of colors of both photo images and 3D objects. NPR is performed based on the reduced colormaps and edge features. To enhance the natural scene presentation, the image region segmentation process is preferred when extracting and applying colormaps. However, the image segmentation technique needs a lot of computational operations. It takes a long time for non-photorealistic rendering for large size frames. To speed up the time-consuming segmentation procedure, we use GPGPU for the parallel computing using the GPU. As a result, we significantly improve the execution speed of the algorithm.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.750-754
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• 2007

본 논문은 실내의 로비나 복도에 설치된 방범 카메라로부터 얻어진 일련의 영상으로부터 '걷기', '뛰기', '앉기', '일어서기', '넘어짐'의 비교적 짧은 시간에 일어나는 인간 행동들을 실시간으로 인식하는 시스템의 구현에 관해 다룬다. 먼저 입력으로 받은 영상을 계층적 색인 구조를 갖는 다중 가우시안 기반의 배경 모델을 이용하여 윤곽을 추출하고 객체를 인식하여 시간차에 의한 가중치로 누적하여 시간 템플릿을 만든다. 만들어진 시간 템플릿으로부터 특징을 추출하여 신경망 모델에 적용하여 5가지 인간행동을 구분한다. 구현된 시스템으로 인간행동 인식 실험을 수행하였는데, 실험 참가자들의 행동 방식이 약간씩 달랐음에도 불구하고 높은 인식률을 보여주었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.215-218
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• 2009

본 논문에서는 웨이블릿 변환 된 고주파 서브밴드들의 에지 정보를 이용하여 관심 객체 영역을 고속으로 자동 검출해주는 새로운 알고리즘을 제안하였다. 제안된 방법에서는 에지정보를 이용하여 블록단위의 4-방향 객체 윤곽 탐색 알고리즘(4-DOBS)을 수행하여 관심객체를 검출한다. 전체 이미지는 $64{\times}64$ 또는 $32{\times}32$ 크기의 코드 블록으로 먼저 나누어지고, 각 코드 블록 내에 에지들이 있는지 없는지에 따라 관심 코드블록 또는 배경이 된다. 4-방향은 바깥쪽에서 이미지의 중앙으로 탐색하여 접근하며, 피사계 심도가 낮은 이미지는 중앙으로 갈수록 에지가 발견된다는 특징을 이용한다. 기존 방법들의 문제점 이였던 복잡한 필터링 과정과 영역병합 문제로 인한 높은 계산도를 상당히 개선시킬 수 있었다. 또한 블록 단위의 처리로 인하여 실시간 처리를 요하는 응용에서도 적용 가능 하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1162-1169
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• 2007

In this paper, we proposed a container identifier recognition method for containers used in harbors. After converting a real container image to a gray image, edges are detected from the gray image applying Prewitt mask and candidate identifier area is extracted using morphological features of individual identifier for identifying containers. Because noises are included in the extracted candidate identifier area, noises are eliminated and each identifier is separated using 4-directional edge tracking algorithm and Grassfire algorithm. Each identifier in the noise-free candidate identifier area is recognized using FCM-based row RBF network for discriminating containers. We used 300 real container images for experiment to evaluate the performance of the proposed method, and we could verify the proposed method is better than a conventional method.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.224-238
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• 2004

Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1106-1109
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• 2012

The stability of object tracking in non-stationary camera environment, such as intelligent surveillance system using a pan/tilt camera, is less stable compared with stationary camera environment. This is due to the fact that it is difficult to model a background image in non-stationary environment. In this letter, we propose a non-stationay pan/tilt camera surveillance system which uses a stop/go procedure together with a real-time active contour. The proposed system can track the object stable even in an environment where only a few difference frames can be obtained.