• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.977-982
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• 2014

In this paper, we propose a system which can detect the flame in real time from the high-quality IP camera. First, open directly the RTSP streams transmitted from the IP camera using the library FFmpeg as opening a video file. The second thing is to extract the background images from video signal using Gaussian mixture model. Then the foreground images are obtained through subtracting operation between the input image and the background image. Separated foreground image through a mathematical morphology operation are considered as candidate area. By analysing colour information and dynamic characteristics of the candidate area, flame is determined finally. Through the experiments with input videos from IP camera, the proposed algorithms were useful to detect flames.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.41-48
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• 2015

Recently, the spread of 3D printers has been increasing the demand for 3D models. However, the creation of 3D models should have a trained specialist using specialized softwares. This paper is about an algorithm to produce a 3D model from a single sheet of two-dimensional front face photograph, so that ordinary people can easily create 3D models. The background and the foreground are separated from a photo and predetermined constant number vertices are placed on the seperated foreground 2D image at a same interval. The arranged vertex location are extended in three dimensions by using the gray level of the pixel on the vertex and the characteristics of eyebrows and nose of the nomal human face. The separating method of the foreground and the background uses the edge information of the silhouette. The AdaBoost algorithm using the Haar-like feature is also employed to find the location of the eyes and nose. The 3D models obtained by using this algorithm are good enough to use for 3D printing even though some manual treatment might be required a little bit. The algorithm will be useful for providing 3D contents in conjunction with the spread of 3D printers.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.485-492
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• 2016

A role of the binarization is very important in separating the foreground and the background in the field of the computer vision. In this study, an adaptive fuzzy binarization is proposed. An ${\alpha}$-cut control ratio is obtained by the distribution of grey level of pixels in a sliding window, and binarization is performed using the value. To obtain the ${\alpha}$-cut, existing thresholding methods which execution speed is fast are used. The threshold values are set as the center of each membership function and the fuzzy intervals of the functions are specified with the distribution of grey level of the pixel. Then ${\alpha}$-control ratio is calculated using the specified function and binarization is performed according to the membership degree of the pixels. The experimental results show the proposed method can segment the foreground and the background well than existing binarization methods and decrease loss of the foreground.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.89-98
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• 2005

간접광고의 한형태인 영화나 드라마 속에 제품배치(PPL)는 온셋 배치와 크리에이티브 배치로 분류할 수 있다. 온셋 배치(on-set placement)는 맥락효과 속에 전경(foreground)에 해당되며, 크리에이티브 배치(creative placement)는 배경에 해당되기 때문에 소비자의 정보처리에 의한 기억효과가 다르게 나타난다. 온셋배치의 경우 자극의 현저성으로 인하여 정교화 가능성 모델이론의 설득의 중심경로를 통한 정보처리효과가 나타나기 때문에 명시적 학습을 하게 된다. 반면에 드라마 배경에 해당하는 PPL의 크리에이티브 배치는 정교화의 수단이 낮아서 배경의 여러 단서들과 함께 설득의 주변경로를 통한 정보처리를 할 것이다. 따라서 암묵적 학습을 할 가능성이 높게 나타나게 된다. 이러한 제품배치의 형태에 따른 학습기억의 형태는 조절변수인 관여도에 따라 다르게 나타날 것이다. 제품관여도가 높은 경우에는 크리에이티브 배치를 하여도 명시적 학습을 할 가능성이 많은 반면 제품관여도가 낮은 경우 크리에이티브 배치를 하게 되면, 암묵적 학습효과가 미약하거나 일어나지 않을 가능성이 많다. 그러므로 제품관여도가 낮은 상품의 경우에는 제품배치시 가능한한 크리에이티브 배치피하는 것이 유리 할 것이다.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.597-609
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• 2008

Due to the recursive updating nature of background model, previous background modeling methods are often perturbed by crowd scenes where foreground pixels occurs more frequently than background pixels. To resolve this problem, an adaptive background modeling method, which is based on the well-known Gaussian mixture background model, is proposed. In the proposed method, the learning rate of background model is adaptively adjusted with respect to the crowdedness of the scene. Consequently, the learning process is suppressed in crowded scene to maintain proper background model. Experiments on real dataset revealed that the proposed method could perform background subtraction effectively even in crowd situation while the performance is almost the same to the previous method in normal scenes. Also, the F-measure was increased by 5-10% compared to the previous background modeling methods in the video of crowded situations.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.527-536
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• 2004

TheReviser is a digital document revision application on a projection display, which allows us to interact a digital document with the same gestures used for paper documents revision. To enable these interactions, TheReviser should detect foreground objects such as hands or pens on a projection display, and should spot and recognize gesture commands from continuous movements of a user. To detect foreground objects from a complex background in various lighting conditions, we perform geometry and color calibration between a captured image and a frame buffer image. TheReviser uses an HMM-based gesture recognition method Experimental results show that the proposed application recognizes user's gestures on average 93.22% in test gesture sequences.

• Journal of the Daesoon Academy of Sciences
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• v.23
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• pp.293-344
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• 2014

본 논문은 『전경』에서는 나타나는 숫자 부호 '삼(三)'의 의미와 나아가 '삼'과 『주역』 그리고 도교 신선신앙과의 연관성을 살펴보고자 한다. 중화의 문화에는 예부터 '삼'을 숭상하는 풍속이 있고, 도교문화도 '삼'을 숭상한다. 이는 주로 『주역』, 『도덕경』 및 도교 신선신앙과 관련이 있다. 한국문화는 전체적으로 중국문화의 영향을 깊이 받았다. 대순진리회 또한 이러한 배경 하에 있다고 볼 수 있다. 대순진리회에서는 '삼' 이라는 숫자를 반복해 사용하고 있는데, 어떤 의미에서 이것은 『주역』에 나타나는 부호 상징 사유의 확장된 표현이라 할 것이다. 또한 대순진리회의 교의(敎義)와 부도(符圖)에서도 '삼을 숭배하는(尙三)' 도교 신선신앙의 특징이 나타나고 있다. 그러므로 대순진리회에서 볼 수 있는 '삼'의 의미는 도교의 영향을 받은 것일 가능성이 매우 크다. 이렇게 말하는 것에는 두 가지 이유가 있는데 그 중 하나는 앞서 말한 바와 같이 대순진리회의 상제와 종도들이 중국의 서적을 이해하고 중시했기 때문이며 대순진리회의 구천상제께서 많은 종교를 통섭하였기 때문이다. 공사(公事) 활동, 부주(符呪) 문건, 상제와 도주의 행적 사료, 신령신앙 등의 내용 곳곳에서 '삼'이라는 특별한 숫자에 대한 각별한 관심이 구체적으로 드러난다. 이러한 '삼'은 생명과 시작을 나타내며 또한 완성과 완결을 의미한다. 대순진리회 신앙의 특징을 보면 그 배후에는 아주 깊은 중국문화의 영향이 있으며, 『주역』사상의 구체적인 표현이고, 도교신선신앙의 흔적이기도 하다. 물론 대순진리회는 자신만의 독창적이 재해석으로 이러한 문화나 사상을 계승하고 발전시켰다. 그렇기 때문에 '삼'이라는 숫자의 근원을 탐구하고, '삼'이 지니고 있는 철학적 사상을 파헤쳐 그 속의 오묘함을 발견한다면 대순사상의 깊을 뜻을 이해하는데 더 큰 도움이 될 것이다.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.206-213
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• 2008

Animation are consist of consecutive various images, and there are figure and ground. The value of figure image as character in animation consider more significant than the background image, it can be detected many literature reviews on that subject. It, however, is also a critical element for completing animation, in reality, it is not found many academical achievements on this subject. The background images imply the information of environment and atmosphere, and elucidates where the story happen, therefore character move, talk and express themselves there. In terms of academic endeavour to extend the knowledge on animation, this paper is one of vital researches to be suggest on background image study. The main purpose of this study is to classify the background images in the ways of three categories such as painting concepts of concrete, semi-abstract, and abstract to camera concept of deep-focus, out-focus, and distortion. It is to instigate for the study of background images, in the practical view. And it will be utilizing the basic theories of cognitive psychology, painting and camera techniques, in the ways of It is analysed to frequency of use, reality, amount of information, perspective, and role of background image. This study is to provide a basic theory of visual classification on background image for practicing animations and researching on this subject.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.45-46
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• 2013

본 논문에서는 깊이 영상과 컬러 영상의 매칭을 통한 강인한 전경 객체 영역화 기법을 제안한다. 기존의 컬러 영상 기반 객체 영역화 알고리즘은 배경과 객체의 색상이 유사한 경우 정확한 객체 영역화가 어렵다. 깊이 영상을 이용하면 이러한 오 검출을 줄일 수 있지만, 깊이 영상 취득 장비의 오류로 인하여 검출되는 객체 외곽선이 컬러 영상에 비해 세밀하지 못한 단점이 있다. 따라서, 깊이 영상의 외곽선을 비교적 세밀한 컬러 영상의 외곽선에 매칭시킨다. 아울러, 서로 다른 센서에서 취득한 두 영상을 매칭하기 위하여, 정규화된 상호연관성(normalized cross correlation)을 유사도 척도로 사용한다. 실험을 통하여 제안하는 알고리즘이 전경 객체 영역화의 오 검출을 줄이며, 동시에 객체 외곽선을 충실히 복원함을 확인한다.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.685-695
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• 2008

This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.