• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.427-430
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• 2005

In this paper, we propose a new post-processing method, based on the theory of the projection onto convex sets (POCS) to reduce the blocking artifacts in decoded images. We propose a new smoothness constraint set (SCS) and its projection operator in the wavelet transform (WT) domain to remove unnecessary high-frequency components caused by blocking artifacts. We also propose a new method to find and preserve the original high frequency components of the image edge. Experimental results show that the proposed method can not only achieve a significantly enhanced subjective quality, but also have the PSNR improvement in the output image.

• 한국음향학회:학술대회논문집
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• 한국음향학회 2000년도 하계학술발표대회 논문집 제19권 1호
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• pp.417-420
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• 2000

점진적 영상 전송과 저해상도에서도 높은 PSNR를 나타내는 방법으로 EZW(Enbeded Zerotree Wavelet)과 SPIHT(set partitioning in hierarchical tree)를 사용한 보다 향상된 영상 압축방법이 제안되어졌다. 특히 SPIHT는 적응 산술부호화(adaptive arithmetic coding)를 사용하지 않고도 EZW보다 뛰어난 압축률과 효과를 얻을 수 있다. 하지만 부대역(subband)간의 유사성(similarity)을 이용한 제로트리 부호화에서 계층을 나누는 일은 계수 사이의 연결관계를 깰 수 있기 때문에 간단한 일은 아니다. 본 논문에서는 SPIHT의 비트열을 여러개의 계층으로 나누고 각각의 해상도로 복원하는 새로운 정렬 방법을 제안하고, 계층간의 비트열을 균일하게 나눔으로써 보다 효율적으로 전송 할 수 있는 방법을 제안하였다. 또한 복호시에 낮은 해상도일수로 복원시간의 이득을 볼 수 있는 향상된 방법을 제안한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.369-371
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• 2009

휴머노이드 로봇에서 스스로 환경을 인식하는 기술은 필수적으로 필요하다. 그러나 정확하게 환경을 인식하기 위해서는 휴머노이드 움직임을 추정하여 보정해야 한다. 따라서 본 논문에서는 type-2 퍼지셋을 이용하여 휴머노이드 로봇의 움직임을 스테레오 비전기반으로 추정하는 방법을 제안하고자 한다. 본 연구에서는 우선 스테레오 비전으로 얻은 Disparity Map을 Type-2 퍼지셋을 이용하여 추적할 대상을 추출한다. 추출된 대상은 보다 정확한 계산을 위하여 Wavelet Transform을 이용하여 정보량을 확장하였으며, 그 결과로 얻어진 결과영상들은 다시 Least suqare approximation과 Type-2 퍼지셋을 이용하여 하나의 결과값으로 나타내어진다. 연속된 두 이미지의 움직임을 추정함으로써 로봇의 움직임을 추정하게 된다. 제안된 방법은 실험을 통하여 그 추정 정확도나 연산속도 면에서 효율적임을 알 수 있었다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1310-1315
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• 2003

In many practical engineering design problems, there are some design and manufacturing considerations that are difficult or infeasible to express in terms of an objective function or a constraint. In this situation, a set of optimal candidate designs having different topological complexities, not just a single optimal design, is preferred. To generate systematically such design candidates, we propose a hierarchical multiscale design resolution control scheme. In order to adjust its topological complexity by choosing a different starting resolution level in the hierarchical design space, we propose to employ a general M-band wavelet transform in transforming the original design space into the multiscale design space.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.227-230
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• 2002

A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

• 한국정보컨버전스학회:학술대회논문집
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• 한국정보컨버전스학회 2008년도 International conference on information convergence
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• pp.103-110
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• 2008

In this thesis, we describe a statistical method for 3D object detection. In this method, we decompose the 3D geometry of each object into a small number of viewpoints. For each viewpoint, we construct a decision rule that determines if the object is present at that specific orientation. Each decision rule uses the statistics of both object appearance and "non-object" visual appearance. We represent each set of statistics using a product of histograms. Each histogram represents the joint statistics of a subset of wavelet coefficients and their position on the object. Our approach is to use many such histograms representing a wide variety of visual attributes. Using this method, we have developed the first algorithm that can reliably detect faces that vary from frontal view to full profile view and the first algorithm that can reliably detect cars over a wide range of viewpoints.

• 경영과학
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• 제24권2호
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• pp.57-72
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• 2007

Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2000년도 가을 학술발표논문집 Vol.27 No.2 (2)
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• pp.209-211
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• 2000

SPIHT(Set Partitioning In Hierarchical Trees) 부호화 알고리즘은 EXW(Embedded Zerotree Wavelet) 부호와 알고리즘의 부호화 방법을 개선하여 압축 효율을 개선한 알고리즘이다. SPIHT 부호화 알고리즘은 웨이브렛 변환된 영상의 계수 값이 동일한 방향은 갖는 대역 사이에서 상관 관계를 갖는다는 점을 이용한다는 점에서 EZW 부호화 알고리즘과 동일하다. 그러나 zerotree의 부호화 부분에서 계수의 중요도에 따라 부분 집합으로 분할해 가는 과정과 분할된 계수들을 부호화하는 과정을 개선하였다. 이 부호화 과정에서의 significant map은 모든 threshold에 대해서 LSP(List of Insignificant Pixels), LIP(List of Insignificant), LIS(List of Insignificant Sets)의 세가지 리스트를 통하여 구하여 진다. 그리고, 전체 알고리즘은 초기화, Sorting pass, Refinement pass, 양자화 값 갱신의 네 가지 단계로 구성된다. 본 논문에서는 SPIHT 구현에 필요한 자료구조를 제안하고 SPIHT 부호화 모듈을 구현에 대하여 설명한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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• pp.187-190
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• 2004

This paper proposes an efficient hardware implementation of SPIHT(Set Partitoning In Hierarchical Tree) algorithm for image compression with the discrete wavelet transform. An efficient technique to scan the coefficients which are located in partitioned spatial orientation trees by DWT is considered in terms of counter fields for sorting pass and refinement pass. The proposed image compression method using SPIHT has been modeled in VHDL and has been implemented by use of both TMS320C6000 as a DSP and Virtex2 as a Xilinx FPGA.

• Journal of Information Processing Systems
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• 제19권2호
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• pp.232-239
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• 2023

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multi-description ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multi-description ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point's position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.