• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.365-368
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• 2011

본 논문에서는 시청자의 색상 특성을 고려하여 양안식 영상에서의 색상 불일치를 예측하는 방법을 제안했다. 먼저 색상 불일치 예측을 위한 주관적 평가로 색상 민감도 평가를 수행했다. 기본 세 채널 색 R, G, B에 대해 각각의 색상의 오차 범위를 결정한 후, 이를 기반으로 관심도와 복잡도를 평가하여 보다 세밀한 주관적 평가를 수행했다. 실험 결과를 통해 제안한 방법이 기존의 색상의 품질을 평가하기 위해 사용하는 유클리디안 색 거리 계산 방법과 US & Canadian Government Printing Offices의 품질 수준 규격(Qulaity Level Specifications)을 이용한 방법보다 효율적으로 색상 불일치 여부를 평가함을 확인했다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.80-82
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• 2010

본 논문에서는 깊이 정보를 이용하여 영상을 색상 분포가 각각 다른 객체 영상으로 분리하고 개별적으로 히스토그램 매칭 기법을 적용하는 조명 보상 기법을 제안한다. 서로 위치가 다른 다시점 카메라의 경우, 다시점 비디오 부호화(multi-view video coding)의 성능을 저하시키는 인접 시점 영상 간 조명 불일치 현상이 발생한다. 이러한 조명 불일치를 보상하기 위한 히스토그램 매칭(histogram matching)을 이용한 전처리 기법이 제안되었다. 모든 시점의 다시점 영상 히스토그램은 정해진 참조 시점 영상의 히스토그램으로 매칭되어 조명 불일치와 다시점 비디오 부호화의 성능을 개선할 수 있다. 하지만 일반적인 영상은 색상 분포와 깊이 정보가 상호 독립적인 객체들로 구성되어 있다. 또한 다시점 비디오는 시점에 따라 획득된 영상 간에 동일 객체의 위치와 깊이가 서로 달라 정해진 참조 시점의 히스토그램으로 매칭하는 기존의 방법은 적합하지 않다. 본 논문에서는 주어진 영상 내에서 깊이 정보를 이용하여 객체를 먼저 분리하고, 객체 영상별로 히스토그램 매칭 기법을 적용하여 색상 보상을 수행하는 새로운 기법을 제안한다. 실험을 통해 제안하는 객체 단위의 조명 보상 기법이 향상된 다시점 비디오 부호화 효율을 보이는 것을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1267-1268
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• 2013

온라인 패션 쇼핑몰을 이용하는 소비자가 늘어나면서 소비자의 불만 사항으로 상품의 불량상태, 사이즈 불일치, 배송 및 환불 지연, 품절 및 입고 지연, 색상 불일치, 입어보지 못하는 불편함 등이 있는데, 그 중에 하나인 사이즈 불일치와 입어보지 못하는 불편함을 가상의 모델로 대체하여 옷을 입어 사용자가 확인하는 어플리케이션이다. 본 논문에서는 사용자의 키와 몸무게, 사이즈를 입력하고 사람의 표준적인 몸으로 사이즈에 맞는 옷을 입혀 사용자가 옷을 사기 전 사이즈를 확인 할 수 있도록 도움을 주는 어플리케이션이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.127-136
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• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.881-886
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• 2013

Even though a multi-view camera system is able to capture multiple images at different viewpoints, the color distributions of captured multi-view images can be inconsistent. This problem decreases the quality of multi-view images and the performance of post-image processes. In this paper, we propose an improved polynomial model for effectively correcting the color inconsistency problem. This algorithm is fully automatic without any pre-process and considers occlusion regions of the multi-view image. We use the 5th order polynomial model to define a relative mapping curve between reference and source views. Sometimes the estimated curve is seriously distorted if the dynamic range of extracted correspondences is quite low. Therefore we additionally estimate the first order polynomial model for the bottom and top regions of the dynamic range. Afterwards, colors of the source view are modified via these models. The proposed algorithm shows the good subjective results and has better objective quality than the conventional color correction algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.651-660
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• 2010

In this paper, we implement an efficient histogram-based prefiltering to compensate the illumination mismatches in regions between neighboring views. In multi-view video, such illumination disharmony can primarily occur on account of different camera location and orientation and an imperfect camera calibration. This discrepancy can cause the performance decrease of multi-view video coding(MVC) algorithm. A histogram matching algorithm can be exploited to make up for these differences in a prefiltering step. Once all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching, the coding efficiency of MVC is improved. However general frames of multi-view video sequence are composed of several regions with different color composition and their histogram distribution which are mutually independent of each other. In addition, the location and depth of these objects from sequeuces captured from different cameras can be different with different frames. Thus we propose a new algorithm which classify a image into several subpartitions by its depth information first and then histogram matching is performed for each region individually. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with the conventional image-based algorithms.

• Journal of Broadcast Engineering
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• v.15 no.6
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• pp.768-782
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• 2010

Because of the different shooting position between multi-view cameras and the imperfect camera calibration, Illumination mismatches of multi-view video can happen. This variation can bring about the performance decrease of multi-view video coding(MVC) algorithm. A histogram matching algorithm can be applied to recompensate these inconsistencies in a prefiltering step. Once all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching, the coding efficiency of MVC is improved. However the histogram distribution can be different not only between neighboring views but also between sequential views on account of movements of camera angle and some objects, especially human. Therefore the histogram matching algorithm which references all frames in chose view is not appropriate for compensating the illumination differences of these sequence. Thus we propose new algorithms both the image classification algorithm which is applied two criteria to improve the correlation between inter-view frames and the histogram matching which references and matches with a group of pictures(GOP) as a unit to advance the correlation between successive frames. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with the conventional algorithms.

• Smart Media Journal
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• v.3 no.4
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• pp.22-27
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• 2014

Three-dimensional image reconstruction allows us to represent real objects in the virtual space and observe the objects at arbitrary view points. This technique can be used in various application areas such as education, culture, and art. In this paper, we propose an implementation method of the high-quality three-dimensional object using multiple Kinect cameras released from Microsoft. First, We acquire color and depth images from triple Kinect cameras; Kinect cameras are placed in front of the object as a convergence form. Because original depth image includes some areas where have no depth values, we employ joint bilateral filter to refine these areas. In addition to the depth image problem, there is an color mismatch problem in color images of multiview system. In order to solve it, we exploit an color correction method using three-dimensional geometry. Through the experimental results, we found that three-dimensional object which is used the proposed method is more naturally represented than the original three-dimensional object in terms of the color and shape.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.77-79
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• 2010

본 논문은 다시점 비디오의 조명 불일치 현상을 효과적으로 보상하기 위한 히스토그램 매칭 기법의 성능을 향상시키는 영상의 에지 방향성을 고려한 전처리 기법을 제안하였다. 다시점 비디오는 카메라 간 서로 다른 위치와 방위로 인해 인접한 시점 영상 간에 존재하는 동일 물체에 색상 차이가 발생할 수 있다. 히스토그램 매칭 기법은 모든 시점 영상의 히스토그램을 정해진 참조시점 영상의 히스토그램에 매칭시켜 다시점 비디오의 조명 불일치 현상을 보상하는 방법이다. 본 논문에서는 히스토그램 매칭을 수행하기 전에 ELA(Edge-based Line Averaging) 선형 보간 기법과 Cosited 대표 값 추출 필터를 결합한 전처리 필터를 선행하여 조명 보상 효과와 다시점 부호화 성능을 향상시켰다. 실험을 통해 제안하는 전처리 기법이 일반적인 다시점 비디오 부호화에 비해 약 2 dB의 평균 PSNR 향상과 34%의 비트율 절감 효과를 가짐을 확인하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.3
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• pp.27-38
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• 2017

This Paper Presents a Method for Stitching a Large Number of Images Recorded by a Large Number of Individual Users Through a Cellular Phone Camera at a Venue. In Contrast to 360 Camera Solutions that Use Existing Fixed Rigs, these Conditions must Address New Challenges Such as Time Synchronization, Repeated Transformation Matrix Calculations, and Camera Sensor Mismatch Correction. In this Paper, we Solve this Problem by Updating the Transformation Matrix Using Time Synchronization Method Using Audio, Sensor Mismatch Removal by Color Transfer Method, and Global Operation Stabilization Algorithm. Experimental Results Show that the Proposed Algorithm Shows better Performance in Terms of Computation Speed and Subjective Image Quality than that of Screen Stitching.