• 한국정보컨버전스학회:학술대회논문집
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• 한국정보컨버전스학회 2008년도 International conference on information convergence
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• 전자공학회논문지CI
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• 제40권1호
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• pp.30-38
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• 2003

본 논문은 비디오 영상에서 움직이는 물체를 분할하는 방법을 제안한다. 물체들의 크기가 작거나 서로 겹쳐있을 경우(occlusion), 또는 잡음이 많은 경우에도 안정적인 이 방법은 움직임 검출(motion detection)과 움직임 분할(motion segmentation) 두 단계로 구성되어 있다. 움직임 검출을 하기 위하여 인접 영상간의 차영상(difference image) 분석을 통해 움직임이 있는 부분을 추출하며, 이때 적응적 임계치 방법을 이용하여 빛의 변화나 노이즈가 포함된 환경에서도 안정적으로 추출한다. 움직임 분할 단계에서는 움직임이 검출된 부분을 초기영역으로 분할 한 뒤, 이 영역들의 모션정보에 따라 이웃 한 영역들을 병합함으로써 독립적으로 움직이는 물체를 분할한다. 이러한 방법은 검출된 영역에 대해서만 움직임 분할을 함으로 많은 계산효과를 얻을 수 있으며 실제 도로영상에서 제안된 방법을 실험해본 결과 비디오 감시시스템에 적합함을 알 수 있었다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권12호
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• pp.683-689
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• 2000

Two-dimensional(2-D) fiber-optic code-division multiple-access(FO-CDMA) system utilizes the optical orthogonal signature pattern code(OOSPC) to encode and decode 2-D data. Encoded 2-D data are spatially multiplexed and transmitted through an image fiber and receiver recovers the intended data by means of thresholding process. OOSPC's construction methods based on expansion of the optical orthogonal code, which is used in one-dimensional(1-D) FO-CDMA system, are introduced. Each OOSPC's performances are compared by using the bit error rate(BER) of interfering OOSPC's of other users. From the results we verify that a balanced incomplete block design(BIBD) construction has the best performance among other mehtods. We also propose a decomposed bit-plane method for parallel transmission and recovery of 256 gray-scale images using OOSPC's constructed by the BIBD method. The simulation result encourages the feasibility of parallel transmission and recovery of multiuser's images.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2014년도 추계 종합학술대회 논문집
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• pp.29-30
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• 2014

본 논문에서는 컨테이너 BIC-code 자동인식 시스템의 전 처리 과정으로서 다중 임계값을 이용한 BIC-code 영역 추출 방법을 제안한다. 기후요소, 빛, 카메라 위치, 컨테이너의 색과 같은 다양한 요인으로 인해 고정된 임계값을 사용할 수 없다. 따라서 각 영상에 대해 다양한 임계값으로 실험하여 컨테이너 BIC-code 인식에 가장 우수한 임계값을 결정하여 영상을 이진화한다. 다음으로, 가장 우수한 임계값으로 이진화 한 영상에 대하여 레이블링, 닫힘 연산을 통해 BIC-code의 가로, 세로 여부를 판단하게 된다. 또한 레이블링 된 각 영역을 판단하여 잡음을 제거하고, 개별 code를 분리한다. 제안된 방법에 대한 실험결과 성공적인 코드 영역 분리가 가능함을 확인할 수 있었다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (2)
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• pp.361-363
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• 2001

반도체 패키지의 마킹검사(marking inspection)를 위해서는 입력 영상으로부터 검사할 패키지의 정확만 위치 검출과 패키지 윗면에 나타난 제작사 로고, 문자, Pin1 딤플의 추출이 필수적이다. 본 연구는 마킹검사를 위한 선행 연구로 마킹검사를 수행할 때, 검사할 IC 패키지의 위치와 방향을 정확하게 검출하는 것을 목적으로 하고 있다. IC 패키지의 외곽을 구성하는 리드의 명도 값은 트레이의 명도 값과 큰 차이를 나타낸다. 그러나 IC 패키지의 방향을 나타내는 Pin1 딤플은 배경과 동일한 색상으로 다만 약간 오목하게 들어가서 명도 값의 차이가 미세하다. 이러한 두 가지 상이한 특징을 효과적으로 처리하기 위하여 적응적 다중 이진화 방법을 제시하였다. 76개의 명도 영상에 대한 실험 결과 제안된 이진화 방법은 매우 효과적이었으며, 이진화된 영상으로부터 IC 패키지의 정확한 위치 검출과 방향 확인이 가능하였다.

• Journal of the Optical Society of Korea
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• 제17권2호
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• pp.188-199
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• 2013

This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions- horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.

• 융합신호처리학회논문지
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• 제15권4호
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• pp.128-134
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• 2014

본 연구에서는 시공간 영상 해석을 이용한 미소혈관내 백혈구 운동의 검출 방법을 제안한다. 혈관벽에 부착하는 백혈구 운동은 영상내 혈관벽의 윤곽선을 따라 움직이는 것으로 시각화될 수 있다. 제안 방법에서 백혈구는 혈관벽의 윤곽선을 따라 움직인다는 구속조건을 사용하며 시공간 영상 해석방법의 사용에 의해 백혈구 운동을 검출한다. 생성된 시공간 영상은 특수한 목적의 방향 선택 필터에 의해 처리되고 후속의 분류처리가 행해진다. 이 후속의 분류처리는 단순한 임계값 및 윤곽선 처리에 의해 획득된 모든 성분중에서 백혈구 궤적 성분을 선택하고 분류한다. 실험 결과, 제안 방법은 복수개의 백혈구 흔적이 서로 교차할 때에도 백혈구 운동을 안정하게 검출할 수 있음을 보여준다.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.423-428
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• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• 대한원격탐사학회지
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• 제10권2호
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• pp.133-160
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• 1994

In this paper, we propose a comprehensive geometric correction algorithm of Along Track Scanning Radiometer(ATSR) images. The procedure consists of two cascaded modules; precorrection and fine co-location. The pre-correction algorithm is based on the navigation model which was derived in mathematical forms. This model was applied for correction raw(un-geolocated) ATSR images. The non-systematic geometric errors are also introduced as the limitation of the geometric correction by this analytical method. A fast and automatic algorithm is also presented in the paper for co-locating nadir and forward views of the ATSR images by using a binary cross-correlation matching technique. It removes small non-systematic errors which cannot be corrected by the analytic method. The proposed algorithm does not require any auxiliary informations, or a priori processing and avoiding the imperfect co-registratio problem observed with multiple channels. Coastlines in images are detected by a ragion segmentation and an automatic thresholding technique. The matching procedure is carried out with binaty coastline images (nadir and forward), and it gives comparable accuracy and faster processing than a patch based matching technique. This technique automatically reduces non-systematic errors between two views to .$\pm$ 1 pixel.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.556-564
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• 2021

Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.