• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.08a
• /
• pp.277-280
• /
• 2000

기존의 웨이브릿 기반 프랙탈 압축 방법은 전 영역에 대하여 최적의 정의역을 탐색하므로, 부호화 과정에서 많은 탐색시간이 소요되는 단점이 있다. 그래서 본 논문에서는 웨이브릿 변환영 역에서 SAS(Self Affine System) 기법을 이용한 웨이브릿 변환 기반 프랙탈 영상 압축 방법을 제안한다. 웨이브릿 변환영역에서 정의역과 치역을 구성하고, 각각의 정의역과 치역에 대해 모든 블록을 탐색하는 것이 아니라, 각 대역별로 공간적으로 같은 위치에 있는 블록을 정의역으로 선택한다. 이와 같이 웨이브릿 변환 영역에서 정의역 탐색과정이 필요 없는 SAS 프랙탈 영상 압축방법을 도입하여 부호화 과정에서 곱셈 계산량을 감소시켜 고속 부호화를 가능하게 하였고, 복호화 과정에서 각 레벨별로 서로 다른 스케일을 사용하여 화질을 개선하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.4
• /
• pp.11-11
• /
• 2001

기존의 웨이브릿 기반 프랙탈 압축 방법은 전 영역에 대하여 최적의 정의역을 탐색하므로, 부호화 과정에서 많은 탐색시간이 소요되는 단점이 있다. 그래서 본 논문에서는 웨이브릿 변환영역에서 SAS(Self Affine System) 기법과 다중 스케일 인자를 이용한 웨이브릿 변환 기반 프랙탈 영상 압축 방법을 제안한다. 웨이브릿 기반 영역에서 정의역과 치역을 구성하고, 각각의 치역 블럭에 대해 모든 정의역 블럭을 탐색하는 것이 아니라, 정의역 탐색과정이 필요 없는 SAS 기법을 도입하여 공간적으로 같은 위치에 있는 상위 레벨 블록을 정의역으로 선택한다 그래서 부호화 과정에서 곱셈 계산량을 감소시켜 고속 부호화를 가능하게 한다. 그리고 SAS 기법의 단점인 화질이 떨어지는 단점을 개선하기 위해, 각 레벨별로 서로 다른 스케일 인자를 사 용하여 화질을 개선한다. 그 결과 화질에는 영향을 미치지 않고 부호화 시간과 압축률이 개선되고, 점진적 전송이 가능한 알고리듬을 제안한다.

• Journal of Korea Multimedia Society
• /
• v.2 no.1
• /
• pp.38-46
• /
• 1999

In this paper, the fractal image compression using the minimizing method of domain region is proposed. It is minimize to domain regions in the process of decoding. Since the conventional fractal decoding applies to IFS(iterative function system) for the total range blocks of the decoded image, its computational complexity is a vast amount. In order to improve this using the number of the referenced times to the domain blocks for the each range blocks, a classification method which divides necessary and unnecessary regions for IFS is suggested. If necessary regions for IFS are reduced, the computational complexity is reduced. The proposed method is to define the minimum domain region that a necessary region for IFS is minimized in the encoding algorithms. That is, a searched region of the domain is limited to the range regions that is similar with the domain regions. So, the domain region is more overlapped. Therefore, there is not influence on image quality or PSNR(peak signal-to-noise ratio). And it can be a fast decoding by reduce the computational complexity for IFS in fractal image decoding.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.2
• /
• pp.13-19
• /
• 2001

The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Journal of the Korea Computer Industry Society
• /
• v.4 no.4
• /
• pp.589-598
• /
• 2003

In the conventional fractal image compression in the DWT(discrete wavelet transform), the domain and range blocks were classified as B${\times}$B block size first before all domain block for each range block was searched. The conventional method has a disadvantages that the encoding time takes too long, since the domain block for entire image was searched. As an enhancement to such inefficiencies and image quality, this paper proposes wavelet-based fractal image compression with multiscale factors. Thus, this proposed method uses multiscale factor along each level and band to enhance an overall image quality. In encoding process of this method, the range blocks are not searched for all the domain blocks; however, using the self affine system the range blocks are selected from the blocks in the upper level. The image qualify of the conventional method is 32.30[dB], and the proposed method is 35.97[dB]. The image quality is increased by 3.67[dB].

• Annual Conference on Human and Language Technology
• /
• 2015.10a
• /
• pp.250-254
• /
• 2015

본 논문은 한국어 의미역을 정의하고, 기계학습에 기반하여 한국어 의미역 인식 기술을 개발할 때 필요한 학습 말뭉치를 구축할 때 지켜야할 가이드라인을 제시하고자 한다. 한국어 의미역 정의는 전세계적으로 널리 쓰이고 있는 Proposition Bank를 따르면서, 한국어의 특성을 반영하였다. 또한 정의된 의미역 및 태깅 가이드라인에 따라 반자동 태깅 툴을 이용하여 말뭉치를 구축하였다.

• Journal of Biomedical Engineering Research
• /
• v.17 no.1
• /
• pp.121-128
• /
• 1996

This paper presents the ECG data compression method referred the adaptive fractal interpolation algorithm. In the previous piecewise fractal interpolation(PFI) algorithm, the size of range is fixed So, the reconstruction error of the PFI algorithm is nonuniformly distributed in the part of the original ECG signal. In order to improve this problem, the adaptive fractal interpolation(AEI) algorithm uses the variable range. If the predetermined tolerance was not satisfied, the range would be subdivided into two equal size blocks. large ranges are used for encoding the smooth waveform to yield high compression efficiency, and the smaller ranges are U for encoding rapidly varying parts of the signal to preserve the signal quality. The suggested algorithm was evaluated using MIT/BIH arrhythmia database. The AEI algorithm was found to yield a relatively low reconstruction error for a given compression ratio than the PFI algorithm. In applications where a PRD of about 7.13% was acceptable, the ASI algorithm yielded compression ratio as high as 10.51, without any entropy coding of the parameters of the fractal code.

• Communications of Mathematical Education
• /
• v.24 no.1
• /
• pp.49-65
• /
• 2010

The purpose of this study is to encourage the role of domain to consider the teaching of the concept of functions in modeling real situations. To do this, it is analyzed that how to introduce the concept of functions and linear functions in textbooks treated in the 1st grade and the 2nd grade of middle school. This study also reviewed the role of domain in representational activities for modeling real situations using linear functions. In these reviews, it found that many textbooks do not consider the domain in the equations of functions and these graphs and several text books used linear functions for modeling real situations which are not represented by linear functions contextually. It is concluded that the domain of function is an important concept that will be considered any representational activities for functions.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.4
• /
• pp.1048-1056
• /
• 1998

In this paper, a fractal image coding based on discrete wavelet transform is proposed to improve PSNR at low bit rates and reduce computational complexity of encoding process. The proposed method takes the absolute value of discrete wavelet transform coefficients, and then constructs significant coefficients trees, which indicate the positions and signs of the significant coefficients. This method improves PSNR and reduces computational complexity of mapping contracted domain pool onto range block, by matching only the significant coefficients of range block to coefficients of contracted domain block. Also, this paper proposes a classification scheme which minimizes the number of contracted domain blocks compared with range block. This scheme significantly reduces the number of range and contracted domain block comparison.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.4
• /
• pp.335-343
• /
• 2001

The conventional wavelet-based fractal image coding has the disadvantage that the encoding takes a long time, since each range block finds the best domain in the image. In this Paper, we propose wavelet-based fractal image coding using SAS(Self Affine System) method and multi-scale factor. It consists of the range and domain blocks in DWT(discrete wavelet transform) region. Using SAS method, the proposed method is that the searching process of the domain block is not required, and the range block selects the domain which is relatively located the same position in the upper level. The proposed method can perform a fast encoding by reducing the computational complexity in the encoding process. In order to improve the disadvantage of SAS method which is reduced image qualify, the proposed method is improved image qualify using the different scale factors for each level. As a result, there is not influence on an image quality, the proposed method is enhanced the encoding time and compression ratio, and it is able to the progressive transmission.