• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.583-587
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• 2009

In this paper we propose a new method of Depth-Image-Based Rendering (DIBR) for Free-viewpoint TV (FTV). In the proposed method, virtual viewpoint images are rendered with 3D warping instead of estimating the view-dependent depth since depth estimation is usually costly and it is desirable to eliminate it from the rendering process. However, 3D warping causes some problems that do not occur in the method with view-dependent depth estimation; for example, the appearance of holes on the rendered image, and the occurrence of depth discontinuity on the surface of the object at virtual image plane. Depth discontinuity causes artifacts on the rendered image. In this paper, these problems are solved by reconstructing disparity information at virtual camera position from neighboring two real cameras. In the experiments, high quality arbitrary viewpoint images were obtained.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.368-372
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• 2009

Pin-hole model has been widely used as a robust tool for easily understanding how to obtain a stereo image and how to present the depth-cue to an observer in stereoscopy. However, most of the processes to analyze depth cue in stereoscopy are performed that a stereo image is taken by camera model practically but depth cue of the image is analyzed by pin-hole model. Therefore, the result of depth cues by the process to be uncorrected. The reason of the uncorrected depth cue is led to the image distances of camera model due to variable focused object distances, and it makes a depth distortion. In this paper, we tried to show the contradiction such as occurring depth distortion in the process which the pin-hole model is used to analyze depth cue despite practical camera model is used in stereoscopy, and we presents the method to overcome the contradiction.

• International Journal of Internet, Broadcasting and Communication
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• 제7권1호
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• pp.15-19
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• 2015

The depth information of an image is used in a variety of applications including 2D/3D conversion, multi-view extraction, modeling, depth keying, etc. There are various methods to acquire depth information, such as the method to use a stereo camera, the method to use the depth camera of flight time (TOF) method, the method to use 3D modeling software, the method to use 3D scanner and the method to use a structured light just like Microsoft's Kinect. In particular, the depth camera of TOF method measures the distance using infrared light, whereas TOF sensor depends on the sensitivity of optical light of an image sensor (CCD/CMOS). Thus, it is mandatory for the existing image sensors to get an infrared light image by bundling several pixels; these requirements generate a phenomenon to reduce the resolution of an image. This thesis proposed a measure to acquire a high-resolution image through gradual area movement while acquiring a low-resolution image through pixel bundling method. From this measure, one can obtain an effect of acquiring image information in which illumination intensity (lux) and resolution were improved without increasing the performance of an image sensor since the image resolution is not improved as resolving a low-illumination intensity (lux) in accordance with the gradual pixel bundling algorithm.

• 반도체디스플레이기술학회지
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• 제21권3호
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• pp.87-91
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• 2022

Bokeh effect is a stylistic technique that can produce blurring the background of photos. This paper implements to produce a bokeh effect with a single image by post processing. Generating depth map is a key process of bokeh effect, and depth map is an image that contains information relating to the distance of the surfaces of scene objects from a viewpoint. First, this work presents algorithms to determine the depth map from a single input image. Then, we obtain a sparse defocus map with gradient ratio from input image and blurred image. Defocus map is obtained by propagating threshold values from edges using matting Laplacian. Finally, we obtain the blurred image on foreground and background segmentation with bokeh effect achieved. With the experimental results, an efficient image processing method with bokeh effect applied using a single image is presented.

• Journal of Multimedia Information System
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• 제4권1호
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• pp.43-50
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• 2017

In this paper, we propose a method which detects the nose and face of certain human by using the depth image. The proposed method has advantages of the low computational complexity and the high accuracy even in dark environment. Also, the detection accuracy of nose and face does not change in various postures. The proposed method first locates the locally protruding part from the depth image of the human body captured through the depth camera, and then confirms the nose through the depth characteristic of the nose and surrounding pixels. After finding the correct pixel of the nose, we determine the region of interest centered on the nose. In this case, the size of the region of interest is variable depending on the depth value of the nose. Then, face region can be found by performing binarization using the depth histogram in the region of interest. The proposed method can detect the nose and the face accurately regardless of the pose or the illumination of the captured area.

• 대한임베디드공학회논문지
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• 제12권6호
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• pp.395-403
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• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

• 방송공학회논문지
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• 제9권3호
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• pp.207-213
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• 2004

최근 영상기반 렌더링 기법 중에서 계층적 깊이영상(layered depth image)에 관한 연구가 주목을 받고 있다. 계층적 깊이영상은 여러 시점에서 생성된 깊이영상을 합하여 하나의 데이터 구조로 만든 것으로, 임의 시점의 영상을 간단한 변형 (warping) 함수를 사용하여 쉽게 생성할 수 있다. 반면, 한 장의 영상이 다시점 깊이 데이터를 포함하므로 용량이 매우 큰 단점이 있다. 본 논문에서는 계층적 깊이영상의 압축 부호화를 위한 새로운 전처리 방법을 제안한다. 계층적 깊이영상은 계층의 수가 늘어나 계층의 후미로 갈수록 화소의 밀도가 낮아지는 현상이 두드러진다. 기존의 방법은 이러한 특성을 이용하기 위해 변환을 수행하기 전에 데이터 모으기 기법을 사용하였지만, 깊이정보 사이의 상관관계를 전혀 고려하지 않았다. 본 논문에서는 이전의 두 값을 연결하는 직선과 현재 값사이의 최단거리를 계산한 후, 이 값으로 현재의 깊이 값을 대체하여 변환 효율을 향상시킨다.

• 대한전자공학회논문지SP
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• 제48권6호
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• pp.1-7
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• 2011

깊이 카메라는 Time-of-Flight (TOF) 기술을 이용하여 장면 내 물체들의 거리 정보를 실시간으로 측정하며, 측정된 값은 깊이 영상으로 출력되어 양안식 혹은 다시점 카메라와 함께 장면의 고화질 깊이 맵을 제작하는 데 사용된다. 그러나 깊이 카메라 자체가 가지는 기술적 한계로 인하여 영상에 잡음과 왜곡이 포함되어 있기 때문에 이를 효과적으로 제거할 수 있는 기술이 요구되며, 처리 된 깊이 카메라 영상은 다양한 방법으로 색상 영상과 융합되어 장면의 깊이 정보를 생성할 수 있다. 본 논문에서는 이와 같이 다시 점 카메라와 깊이 카메라를 함께 사용하여 고화질의 깊이 정보를 획득할 수 있는 혼합형 카메라 방식의 원리와 깊이 영상 처리 및 깊이 생성을 위한 기술 동향을 설명한다.

• 방송공학회논문지
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• 제11권1호
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• pp.91-99
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• 2006

전처리는 영상의 질을 개선하거나 영상을 특정한 응용 목적에 알맞도록 변환시키는 등의 영상 처리를 의미한다. Depth 카메라로부터 획득한 화소단위의 8비트 깊이 정보 (depth map) 에는 depth 카메라의 특성상 잡음으로 생각할 수 있는 많은 성분들이 포함되어 있고, RGB 정보에서의 윤곽선에 비해 물체의 특성이나 조명 조건에 의해서 왜곡되어 나타난다. 일반적으로 잡음 제 거 필터가 사용되지만, 이는 깊이 정보 내의 잡음만을 줄이는 역할을 하기 때문에 깊이 정보의 왜곡된 윤곽선 처리는 하지 못 하고 있다. 본 논문에서는 깊이 정보의 잡음을 줄이는 동시에 RGB 정보의 윤곽선을 이용하여 깊이 정보의 왜곡된 윤곽선을 개선하는 알고리즘을 제안함으로써 다시점 입체 영상 생성 시 오차를 줄이고자 한다.

• Journal of Computational Design and Engineering
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• 제3권3호
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• pp.191-197
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• 2016

Since 3D measurement technologies have been widely used in manufacturing industries edge detection in a depth image plays an important role in computer vision applications. In this paper, we have proposed an edge detection process in a depth image based on the image based smoothing and morphological operations. In this method we have used the principle of Median filtering, which has a renowned feature for edge preservation properties. The edge detection was done based on Canny Edge detection principle and was improvised with morphological operations, which are represented as combinations of erosion and dilation. Later, we compared our results with some existing methods and exhibited that this method produced better results. However, this method works in multiframe applications with effective framerates. Thus this technique will aid to detect edges robustly from depth images and contribute to promote applications in depth images such as object detection, object segmentation, etc.