• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.454-460
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• 2000

To retrieve complex data such as images, the content-based retrieval method rather than keyword based method is required. In this paper, we implemented a content-based image retrieval system which retrieves object of user query effectively using invariant moments which have invariant properties about linear transformation like position transition, rotation and scaling. To extract the shape feature of objects in an image, we propose a labeling algorithm that extracts objects from an image and apply invariant moments to each object. Hashing method is also applied to reduce a retrieval time and index images effectively. The experimental results demonstrate the high retrieval efficiency i.e precision 85%, recall 23%. Consequently, our retrieval system shows better performance than the conventional system that cannot express the shale of objects exactly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.281-284
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• 2010

In this paper, we present Hand-gesture recognition for actual computing into color images from camera. Color images are binarization and labeling by using the YCbCr Color model. Respectively label area seeks the center point of the hand from to search Maximum Inscribed Circle which applies Voronoi-Diagram. This time, searched maximum circle and will analyze the elliptic ingredient which is contiguous so a hand territory will be able to extract. we present the presentation contral system using elliptic element and Maximum Inscribed Circle. This algorithm is to recognize the various environmental problems in the hand gesture recognition in the background objects with similar colors has the advantage that can be effectively eliminated.

• Annual Conference of KIPS
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• 2006.11a
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• pp.117-120
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• 2006

뼈 나이 평가는 소아 뼈의 골화정도, 내분비선 장애 등을 쉽게 알아 볼 수 있어 소아 방사선 의학에서 자주 사용되는 방법이다. 뼈 나이 평가를 위해서는 골단판과 손마디 뼈의 길이 넓이 등 뼈 정보가 필요하기 때문에 골단판 영역의 추출이 선행되어야 한다. 하지만 골단판의 성장이 많이 진행되어 손마디 뼈 부분과 붙어 있는 경우 골단판 추출이 어려운 점이 있다. 본 논문에서는 골단판 성장 여부와 상관없이 다양한 나이의 디지털 X-ray 영상에서 손가락의 골단판을 추출하는 알고리즘을 제안한다. 손가락 경계선의 레이블링 처리를 이용하여 정확한 손가락 영역을 추출하고 골단판 위치의 통계적 특성을 사용하여 골단판의 후보 지역을 생성한다. 그리고 골단판 영역에서는 손가락 영상의 수직 투영 미분값이 크기 때문에 후보 지역 내에서 수직 투영 미분값의 변화량으로 골단판의 위치를 정확하게 추출한다. 다양한 나이에 대해 실험해 본 결과 제안한 방법은 골단판의 성장 여부와 상관없이 골다판과 손가락 뼈가 붙은 곳에서도 골단판의 통계적 특성을 사용해 정확한 골단판 영역을 추출할 수 있었다.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.79-87
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• 2021

In this paper, we analysis the semi-supervised learning (SSL), which is adopted in order to train a deep learning-based classification model using the small number of labeled data. The conventional SSL techniques can be categorized into consistency regularization, entropy-based, and pseudo labeling. First, we describe the algorithm of each SSL technique. In the experimental results, we evaluate the classification accuracy of each SSL technique varying the number of labeled data. Finally, based on the experimental results, we describe the limitations of SSL technique, and suggest the research direction to improve the classification performance of SSL.

• Annual Conference of KIPS
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• 2010.04a
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• pp.478-481
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• 2010

컴퓨터 비전에서 객체의 인식, 추적에 앞서 배경으로부터 전경을 분리하는 배경차감 기법과 분리된 전경에 대한 관심 영역(ROI)을 추출하는 것은 일반적인 방법이다. 하지만 전경을 정확히 분리하지 못하면 개별 객체의 관심영역(ROI) 역시 잘못 추출되는 문제가 발생된다. 본 논문에서는 정확하지 않은 전경 분리로 부터 발생되는 개별 객체에 대한 분산된 관심영역을 병합하는 방법을 제안한다. 본 방법은 배경과 분리된 전경에서 한 객체의 일정 거리 이내에 있는 다른 객체를 가상으로 병합하는 단계, 워터쉐드 분할 알고리즘을 적용하는 단계를 거쳐 다시 블럽 레이블링을 수행한다. 제안 방법을 통하여 배경 모델에서 분리된 개별 객체의 병합된 관심영역을 제공한다. 실험에서 기존의 일반적인 블럽 레이블링 방법만을 적용하여 추출한 전경영역과 제안하는 방법에 의한 전경영역을 비교하여 배경 모델에서 분리된 개별 객체의 관심영역이 효과적으로 추출되는 것을 보인다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.119-121
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• 2022

본 논문은 실내가구 인테리어를 배치하는데 있어 증강현실 기술을 적용하여 작업의 효율성을 높일 수 있는 모델을 연구하였다. 현재 증강현실을 적용하는 프로세스에서는 가구의 이미지를 출력할 때 기업의 규모나 제품의 성격 등에 따라 정보가 제한적으로 제공되는 문제를 안고 있다. 이러한 문제점을 해결하기 위하여 본 논문에서 제시하는 알고리즘을 이용하여 AR 레이블링을 생성함으로써, 가구의 정확한 이미지 추출과 함께 가구에 대한 상세한 정보를 제공 받아 사용자가 원하는 가구들을 증강현실을 통해 쉽게 배치할 수 있도록 하는 연구를 진행하였다. 본 연구는 AR 레이블링의 설계, 구현과 3D 렌더링을 통해 원하는 가구들을 실내에 정확히 배치할 수 있어 소비자의 만족도와 구매욕구를 충족시킬 수 있을 것으로 기대된다.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.33-40
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• 2017

In this paper, we propose a text extraction method by pattern analysis on contour for effective text detection in image. Text extraction algorithms using edge based methods show good performance in images with simple backgrounds, The images of complex background has a poor performance shortcomings. The proposed method simplifies the color of the image by using K-means clustering in the preprocessing process to detect the character region in the image. Enhance the boundaries of the object through the High pass filter to improve the inaccuracy of the boundary of the object in the color simplification process. Then, by using the difference between the expansion and erosion of the morphology technique, the edges of the object is detected, and the character candidate region is discriminated by analyzing the pattern of the contour portion of the acquired region to remove the unnecessary region (picture, background). As a final result, we have shown that the characters included in the candidate character region are extracted by removing unnecessary regions.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.17-22
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• 2009

DaVinci processors are popular media processors for implementing embedded multimedia applications. They support dual core architecture: ARM9 core for video I/O handling as well as system management and peripheral handling, and DSP C64+ core for effective digital signal processing. In this paper, we propose our efforts for optimal implementation of object tracking algorithm in DaVinci-based smart camera which is being designed and implemented by our laboratory. The smart camera in this paper is supposed to support object detection, object tracking, object classification and detection of intrusion into surveillance regions and sending the detection event to remote clients using IP protocol. Object tracking algorithm is computationally expensive since it needs to process several procedures such as foreground mask extraction, foreground mask correction, connected component labeling, blob region calculation, object prediction, and etc. which require large amount of computation times. Thus, if it is not implemented optimally in Davinci-based processors, one cannot expect real-time performance of the smart camera.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.35-43
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• 2004

In this paper, we proposed a vehicle recognition and electronic toll collection system with detection and classification of vehicle identification mark and emblem as well as recognition of vehicle license plate to unman toll fee collection system or incoming/outcoming vehicles to an institution. In the proposed algorithm, we first process pre-processing step such as noise reduction and thinning from the rear side input image of vehicle and detect vehicle mark, emblem and license plate region using intensity variation informations, template masking and labeling operation. And then, we classify the detected vehicle features regions into vehicle mark and emblem as well as recognize characters and numbers of vehicle license plate using hybrid and seven segment pattern vector. To show the efficiency of the proposed algorithm, we tested it on real vehicle images of implemented vehicle recognition system in highway toll gate and found that the proposed method shows good feature detection/classification performance regardless of irregular environment conditions as well as noise, size, and location of vehicles. And also, the proposed algorithm may be utilized for catching criminal vehicles, unmanned toll collection system, and unmanned checking incoming/outcoming vehicles to an institution.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.131-139
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• 2009

The existing vessel monitoring system using the ground surveillance radar has a difficulty in monitoring ships continuously due to the limited range of detecting ships. For resolving this problem, we carry out a research on ship detection which is to be the core technology of vessel monitoring system for ocean monitoring using SAR imagery. There are two different methods of detecting ships in SAR imagery: detection of the ship target itself and detection of the ship wake. In this paper, we mainly focus on algorithms which detect the ship itself, and also present the accuracy test after extracting positional and directional figures of the ships. After rectifying input SAR imagery using polynomial transformation, we use Wiener filter to remove speckle noises. A labeling technique and morphological filtering in conjunction with Otsu's method are used to automatically detect the ships based on the image processing domain. For ground truth data, information from a radar system is used, which allows assessing the accuracy of the proposed method. The results show that the proposed method has the high potential in automatically detecting the ships and its positional/directional figures in a fast way.