• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.333-334
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• 2006

In this study, information compression based on the wavelet technique is described. The principle of signal or image compression is performed by optimization of quantization, that is the bit allocation taking advantage of their energy concentration in low frequency components. The wavelet transform is one of frequency decomposition, such as the discrete cosine transform or sub-band filtering, and it is also implemented as a filter bank. Wavelet transform with use of spatially localized basis function can reduce several drawbacks in conventional methods. The benifit of wavelet based compression method is described as comparing the transform method to another ones.

• 대한전자공학회논문지
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• 제25권12호
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• pp.1513-1521
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• 1988

BMA, which is generally adopted in low bit-rate motion-compensated coding, performs properly under an assumption of rigid-body motion of moving objects. Since, however, the assumption can not be held in practical coding , the prediction errors with low correlation are generated. For effective transform codings of the interframe prediction errors, we propose a new transform coding technique which decomposes the prediction errors into two sources and then transforms them with DCT and WHT consecutively. The performance of the proposed algorithm is compared to those of the two conventional algorithms in terms of bit rate and subjective image quality.

• 전자공학회논문지S
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• 제35S권7호
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• pp.62-71
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• 1998

In this paper, we describe the object-oriented motioncompensation technique using the hierarchical grid interpolation(HGI). By noting that the HGI does not exploit effetively the rate-distortion (R-D) trade-off inherent in the quadtree decomposition, we propose an objectoriented HGI technique employing the greedy method. In the proposed technique, input image is decomposed in a quadtree basis using the greedy method, yielding maximum split gain in the R-D sense. Then, the motion compensation is performed using the HGI technique. The performance of the proposed technique is examined in simulation, and it will be show that the proposed technique provides better performance than the conventional object-oriented motion compensation techniques.

• 반도체디스플레이기술학회지
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• 제8권1호
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• pp.43-48
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• 2009

We have examined the problem of the number of quad-tree blocks that an n-dimensional rectangle will be decomposed into on the average. the contribution of this paper are both practical and theoretical. In this paper, we develops the overlapping multi-scale models and the region quad-tree models which is useful in computer graphics animation, image processing, pattern recognition and also for modeling three dimensional objects. These models, which represent something of a conceptual departure from other models developed for multi-scale framework were developed with the specific interest of producing smooth estimates.

• 대한수학회보
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• 제59권6호
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• pp.1327-1337
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• 2022

Zero-difference balanced (ZDB) functions can be applied to many areas like optimal constant composition codes, optimal frequency hopping sequences etc. Moreover, it has been shown that the image set of some ZDB functions is a regular partial difference set, and hence provides strongly regular graphs. Besides, perfect nonlinear functions are zero-difference balanced functions. However, the converse is not true in general. In this paper, we use the decomposition of cyclotomic polynomials into irreducible factors over 𝔽_p, where p is an odd prime to generalize some recent results on ZDB functions. Also we extend a result introduced by Claude et al. [3] regarding zero-difference-p-balanced functions over 𝔽_pⁿ. Eventually, we use these results to construct some optimal constant composition codes.

• 융합신호처리학회논문지
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• 제11권4호
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• pp.270-277
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• 2010

BAMS(Baysian Adaptive Multiresolution Smoother) 필터는 모의실험 없이 Bayes 추정에 기초한 웨이블릿 축소기법에 의해 잡음을 제거하며 따라서 실시간 처리가 가능하다. BAMS 필터에 의한 영상잡음 제거 성능은 웨이블릿 분해 각 대역의 잡음분산에 크게 의존한다. 기존의 BAMS 필터는 웨이블릿 분해의 고주파 대역에서 사분위 통계량을 이용하여 잡음분산을 추정하여 잡음을 제거하였다. 본 논문에서는 영상신호의 중간대역을 포함한 잡음제거를 위해 변형된 사분위 통계량 및 모노토닉 변환으로 중간대역 잡음편차 추정하고 이를 이용해서 중간대역 및 고주파 대역의 영상잡음을 제거한 결과 중간대역의 잡음을 제거하므로 약 2[dB]정도의 PSNR이 증가하였으며 잡음편차가 작은 영상의 잡음제거에서도 효과가 있었다.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1157-1165
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• 2017

2-D complex Gabor filtering has found numerous applications in the fields of computer vision and image processing. Especially, in some applications, it is often needed to compute 2-D complex Gabor filter bank consisting of the 2-D complex Gabor filtering outputs at multiple orientations and frequencies. Although several approaches for fast 2-D complex Gabor filtering have been proposed, they primarily focus on reducing the runtime of performing the 2-D complex Gabor filtering once at specific orientation and frequency. To obtain the 2-D complex Gabor filter bank output, existing methods are repeatedly applied with respect to multiple orientations and frequencies. In this paper, we propose a novel approach that efficiently computes the 2-D complex Gabor filter bank by reducing the computational redundancy that arises when performing the Gabor filtering at multiple orientations and frequencies. The proposed method first decomposes the Gabor basis kernels to allow a fast convolution with the Gaussian kernel in a separable manner. This enables reducing the runtime of the 2-D complex Gabor filter bank by reusing intermediate results of the 2-D complex Gabor filtering computed at a specific orientation. Experimental results demonstrate that our method runs faster than state-of-the-arts methods for fast 2-D complex Gabor filtering, while maintaining similar filtering quality.

• 한국컴퓨터그래픽스학회논문지
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• 제17권4호
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• pp.11-21
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• 2011

본 논문은 한글 외곽선 폰트를 입력으로 글자의 초성, 중성, 종성 요소(컴포넌트)를 통계적-구조적 정보를 이용하여 분할하는 방법을 제안한다. 한 폰트 내에서 한글 컴포넌트는 통계적으로 일정한 위치에 나타나며, 각 컴포넌트를 이루는 획 간의 관계는 그 컴포넌트의 구조적 특징을 나타낸다. 우리는 먼저 각 컴포넌트의 위치를 저장하는 컴포넌트 히스토그램을 생성하여 컴포넌트 위치에 관한 통계 정보를 저장하였다. 그리고 글자의 구조적 정보를 반영하기 위해 픽셀의 방향성 확률을 기반으로 픽셀클러스터를 만들고, 클러스터의 위치, 방향 및 크기, 클러스터간 인접성 정보를 이용하여 후보 획을 추출하였다. 마지막으로 릴렉세이션 레이블링을 통해 후보 획 집합과 미리 정의된 글자 모델 간의 가장 적합한 구조적 매치를 구하였다. 본 논문에서 제안한 컴포넌트 분할방법은 한글 폰트의 조형적 특징에 관한 연구 및 이를 활용한 폰트분류 빛 폰트검색에 활용될 수 있다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1999년도 춘계종합학술대회
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• pp.185-191
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• 1999

Mathematical morphology based on set theory has been applied to various areas in image processing. Pitas proposed a object recognition algorithm using Morphological Shape Decomposition(MSD), and a new representation scheme called Morphological Shape Representation(MSR). The Pitas's algorithm is a simple and adequate approach to recognize objects that are rotated 45 degree-units with respect to the model object. However, this recognition scheme fails in case of random rotation. This disadvantage may be compensated by defining small angle increments. However, this solution may greatly increase computational complexity because the smaller the step makes more number of rotations to be necessary. In this paper, we propose a new method for object recognition based on MSD. The first step of our method decomposes a binary shape into a union of simple binary shapes, and then a new tree structure is constructed which ran represent the relations of binary shapes in an object. finally, we obtain the feature informations invariant to the rotation, translation, and scaling from the tree and calculate matching scores using efficient matching measure. Because our method does not need to rotate the object to be tested, it could be more efficient than Pitas's one. MSR has an intricate structure so that it might be difficult to calculate matching scores even for a little complex object. But our tree has simpler structure than MSR, and easier to calculated the matchng score. We experimented 20 test images scaled, rotated, and translated versions of five kinds of automobile images. The simulation result using octagonal structure elements shows 95% correct recognition rate. The experimental results using approximated circular structure elements are examined. Also, the effect of noise on MSR scheme is considered.

• 대한전자공학회논문지SP
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• 제40권6호
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• pp.31-40
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• 2003

대부분의 얼굴인식 시스템은 현재 2차원 영상을 기반으로 많은 분야에 응용되고 있다. 그러나 2차원 얼굴인식 시스템은 심하게 변화된 얼굴 포즈에 강인한 얼굴인식이 매우 어렵다. 이에 얼굴 포즈 추정은 정면 영상이 아닐 경우 인식률 향상을 위한 필수적인 과정이라 할 수 있다. 그러므로, 본 논문은 3차원 얼굴인식을 위한 새로운 얼굴 포즈 추정 방식을 제안한다 먼저 3차원 거리(range) 영상이 입력될 때 얼굴 곡선에 기반한 자동 얼굴 특징점 추출 기법을 적용한다. 추출된 특징점을 바탕으로 오류 보상 특이치 분해를 적용 한 새로운 3차원 얼굴 포즈 추정 방식을 제안한다. 특이치 분해를 이용하여 초기 회전각을 획득한 후 존재하는 오류를 보다 세밀하게 보상한다. 제안 알고리즘은 정규화된 3차원 얼굴 공간에서 추출된 특징점의 기하학적 위치를 이용하여 수행된다. 또한 3차원 얼굴인식을 위하여 3차원 최근접 이웃 분류기를 이용한 데이터베이스내에서 후보 얼굴을 선택하는 방식을 제안한다. 실험 결과를 통해 다양한 얼굴 포즈에 대하여 제안 알고리즘의 효율성과 타당성을 검증하였다.