• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.124-125
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• 2021

최근 증강현실(AR), 가상현실(VR), 혼합현실(XR) 분야가 각광받고 있으며, 3차원 공간과 사물을 인식하여 다양한 콘텐츠 서비스를 제공하는 기술이 개발되고 있다[1]. 3차원 공간과 사물을 인식하기 위해 가장 널리 사용되는 방법은 RGB 카메라를 이용하는 것이다[2]. RGB 카메라를 이용하여 촬영한 영상을 분석한 후 분석된 결과를 이용하여 카메라와 환경의 관계를 추정한다. 시차는 사용자가 촬영한 복수의 이미지에서 특징점의 차이를 이용하여 계산된다. 실험적으로 구한 깊이에 대해 계산된 디스패리티에 시차 정보와 스케일링 정보를 더하여 3차원 특징점을 생성한다. 제안하는 알고리즘은 단일 모바일 디바이스에서 획득한 영상을 사용한다. 특징점 매칭을 기반으로한 디스패리티 추정과 시차조정 3D 특징점 생성이다. 실제 깊이 값과 비교했을 때, 생성된 3차원 특징점은 실측값의 10% 이내의 오차가 있음을 실험적으로 증명하였다. 따라서 제안하는 방법을 이용하여 유효한 3차원 특징점을 생성할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.78-79
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• 2022

In this paper, we propose a technique for tracking the classification and location of each user through body proportion analysis of the normalized skeletons of multiple users obtained using RGB-D cameras. To this end, each user's 3D skeleton is extracted from the 3D point cloud and body proportion information is stored. After that, the stored body proportion information is compared with the body proportion data output from the entire frame to propose a user classification and location tracking algorithm in the entire image.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.1-11
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• 1998

One of the desired features for the realizations of high quality Information and Telecommunication services in future is "the Sensation of Reality". This will be achieved only with the visual communication based on the 3- dimensional (3-D) moving images. The main difficulties in realizing 3-D moving image communication are that there is no developed data transmission technology for the hugh amount of data involved in 3-D images and no established technologies for 3-D image recording and displaying in real time. The currently known stereoscopic imaging technologies can only present depth, no moving parallax, so they are not effective in creating the sensation of the reality without taking eye glasses. The more effective 3-D imaging technologies for achieving the sensation of reality are those based on the multiview 3-D images which provides the object image changes as the eyes move to different directions. In this paper, a multiview 3-D imaging system composed of 8 CCD cameras in a case, a RGB(Red, Green, Blue) beam projector, and a holographic screen is introduced. In this system, the 8 view images are recorded by the 8 CCD cameras and the images are transmitted to the beam projector in sequence by a signal converter. This signal converter converts each camera signal into 3 different color signals, i.e., RGB signals, combines each color signal from the 8 cameras into a serial signal train by multiplexing and drives the corresponding color channel of the beam projector to 480Hz frame rate. The beam projector projects images to the holographic screen through a LCD shutter. The LCD shutter consists of 8 LCD strips. The image of each LCD strip, created by the holographic screen, forms as sub-viewing zone. Since the ON period and sequence of the LCD strips are synchronized with those of the camera image sampling adn the beam projector image projection, the multiview 3-D moving images are viewed at the viewing zone.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.294-296
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• 2010

일반적으로, RGB 영상의 높은 주파수 영역은 잡음으로 인해 색평면 간 서로 낮은 상관도를 가지고 있기 때문에 이러한 고주파수 성분은 색평면 간 예측의 효율을 저하시키는 원인이 된다. 본 논문에서는 RGB 비디오 코딩에서 색평면 간 예측의 효율을 높이기 위해 기저 색평면을 적응적으로 필터링 하는 방법을 제안한다. 색평면 간 상관도에 따라 적응적으로 기저 색평면을 필터링함으로써 색평면 간 예측 성능을 높일 수 있었다. 본 논문에서 제안하는 알고리즘을 통해 우리는 H.264/AVC High 4:4:4 Intra Profile에 비해 평균 14.71%의 비트율 감소와 0.93dB의 PSNR 향상 결과를 얻을 수 있었다.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.629-639
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• 2017

Interpolation based information hiding methods are widely used to get information security. Conventional interpolation methods use the neighboring pixel value and simple calculation like average to embed secret bit stream into the image. But these information hiding methods are not appropriate to color images like military images because the characteristics of military images are not considered and these methods are restricted in grayscale images. In this paper, the new information hiding method based on interpolation using RGB pixel values of color image is proposed and the effectiveness is analyzed through experiments.

• Spatial Information Research
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• v.13 no.2 s.33
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• pp.129-138
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• 2005

In this paper, a 3D position tracking algorithm for a moving objects using a stereo CCD cameras was proposed. This paper purposed the method to extract the coordinates of the moving objects. That is improve the operating and data processing efficiency. We were applied the relative orientation far the stereo CCD cameras and image coordinates extraction in the left and right images after the moving object segmentation. Also, it is decided on 3D position far moving objects using an acquired image coordinates in the left and right images. We were used independent relative orientation to decide the relative location and attitude of the stereo CCD cameras and RGB pixel values to segment the moving objects. To calculate the coordinates of the moving objects by space intersection. And, We conducted the experiment the system and compared the accuracy of the results.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.113-121
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• 2013

In this paper, we propose a sub-pixel rendering algorithm using learning-based 2D FIR filters. The proposed algorithm consists of two stages: the learning and synthesis stages. At the learning stage, we produce the low-resolution synthesis information derived from a sufficient number of high/low resolution block pairs, and store the synthesis information into a so-called dictionary. At the synthesis stage, the best candidate block corresponding to each input high-resolution block is found in the dictionary. Next, we can finally obtain the low-resolution image by synthesizing the low-resolution block using the selected 2D FIR filter on a sub-pixel basis. On the other hand, we additionally enhance the sharpness of the output image by using pre-emphasis considering RGB stripe pattern of display. The simulation results show that the proposed algorithm can provide significantly sharper results than conventional down-sampling methods, without blur effects and aliasing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.519-525
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• 2022

The face detection task of detecting a person's face in an image is used as a preprocess or core process in various image processing-based applications. The neural network models, which have recently been performing well with the development of deep learning, are dependent on 2D images, so if noise occurs in the image, such as poor camera quality or pool focus of the face, the face may not be detected properly. In this paper, we propose a face detection method that uses depth information together to reduce the dependence of 2D images. The proposed model was trained after generating and preprocessing depth information in advance using face detection dataset, and as a result, it was confirmed that the FRN model was 89.16%, which was about 1.2% better than the RetinaNet model, which showed 87.95%.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.431-438
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• 2016

In this paper, we present an upsampling technique for depth map image using color and depth weights. First, we construct a high-resolution image using the bilinear interpolation technique. Next, we detect a common edge region using RGB color space, HSV color space, and depth image. If an interpolated pixel belongs to the common edge region, we calculate weighting values of color and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.423-431
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• 2009

There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.