• 제목/요약/키워드: Additive Algorithm

검색결과 306건 처리시간 0.025초

변형된 계수 마스크를 이용한 에지 검출 방법 (Edge Detection Method using Modified Coefficient Masks)

  • 이창영;정석문;김남호
    • 전자공학회논문지
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    • 제50권5호
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    • pp.218-223
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    • 2013
  • 에지를 검출하기 위한 기존의 방법에는 Sobel, Prewitt, LoG(Laplacian of Gaussian) 등이 있으며, 이러한 방법들은 AWGN(additive white Gaussian noise)이 첨가된 영상에서 에지 검출 특성이 다소 미흡하다. 따라서 본 논문에서는 기울기 및 거리 가중치 마스크가 적용된 변형된 계수 마스크를 이용한 에지 검출 알고리즘을 제안하였다. 제안된 알고리즘의 성능을 확인 및 검증하기 위하여, 표준편차 ${\sigma}$=15, 30의 AWGN이 첨가된 여러 표준 영상으로 기존의 방법과 비교 및 시뮬레이션하였으며, 처리된 영상에서 제안한 알고리즘은 에지 검출 특성이 우수하였다.

AWGN에 훼손된 영상복원을 위한 복합 필터 알고리즘에 관한 연구 (A Study on Mixed Filter Algorithm for Restoration of Image Corrupted by AWGN)

  • ;김남호
    • 한국정보통신학회논문지
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    • 제16권5호
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    • pp.1064-1070
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    • 2012
  • 현재, 영상처리는 다양한 분야에서 활용되고 있으며, 영상의 우수한 화질을 위해 열화현상을 제거하여야 한다. 잡음은 열화현상의 대표적인 원인으로서, 영상은 AWGN(additive white Gaussian noise)에 의해 많이 훼손된다. 따라서 본 논문에서는 AWGN을 제거하기 위해, 공간영역에서의 워너 필터와 웨이브렛 영역에서의 임계값 잡음 처리방법을 병렬 연결하여 처리하는 복합 필터 알고리즘을 제안하였다. 웨이브렛 영역에서의 처리방법은 각 스케일에 따라 서로 다른 thresholding function을 사용하여 처리하며, 제안한 변형된 thresholding function은 parent 웨이브렛 계수와 child 웨이브렛 계수를 이용함으로서, 우수한 잡음제거 특성을 나타냈다.

Tuning the Architecture of Support Vector Machine: The Case of Bankruptcy Prediction

  • Min, Jae-H.;Jeong, Chul-Woo;Kim, Myung-Suk
    • Management Science and Financial Engineering
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    • 제17권1호
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    • pp.19-43
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    • 2011
  • Tuning the architecture of SVM (support vector machine) is to build an SVM model of better performance. Two different tuning methods of the grid search and the GA (genetic algorithm) have been addressed in the literature, each of which has its own methodological pros and cons. This paper suggests a combined method for tuning the architecture of SVM models, which employs the GAM (generalized additive models), the grid search, and the GA in sequence. The GAM is used for selecting input variables, and the grid search and the GA are employed for finding optimal parameter values of the SVM models. Applying the method to a bankruptcy prediction problem, we show that SVM model tuned by the proposed method outperforms other SVM models.

An Adaptive JPEG Steganographic Method Based on Weight Distribution for Embedding Costs

  • Sun, Yi;Tang, Guangming;Bian, Yuan;Xu, Xiaoyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권5호
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    • pp.2723-2740
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    • 2017
  • Steganographic schemes which are based on minimizing an additive distortion function defined the overall impacts after embedding as the sum of embedding costs for individual image element. However, mutual impacts during embedding are often ignored. In this paper, an adaptive JPEG steganographic method based on weight distribution for embedding costs is proposed. The method takes mutual impacts during embedding in consideration. Firstly, an analysis is made about the factors that affect embedding fluctuations among JPEG coefficients. Then the Distortion Update Strategy (DUS) of updating the distortion costs is proposed, enabling to dynamically update the embedding costs group by group. At last, a kind of adaptive JPEG steganographic algorithm is designed combining with the update strategy and well-known additive distortion function. The experimental result illustrates that the proposed algorithm gains a superior performance in the fight against the current state-of-the-art steganalyzers with high-dimensional features.

시스템잡음에 강건한 SOM-TVC 기법을 이용한 근전도 패턴 인식에 관한 연구 (A Study on the EMG Pattern Recognition Using SOM-TVC Method Robust to System Noise)

  • 김인수;이진;김성환
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권6호
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    • pp.417-422
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    • 2005
  • This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods.

더해지는 기준신호를 이용한 위성복원: I. 이론 (Phase Retrieval Using an Additive Reference Signal: I. Theory)

  • Woo Shik Kim
    • 전자공학회논문지B
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    • 제31B권5호
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    • pp.26-33
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    • 1994
  • Phase retrieval is concerned with the reconstruction of a signal from its Fourier transform magnitude (or intensity), which arises in many areas such as X-ray crystallography, optics, astronomy, or digital signal processing. In such areas, the Fourier transform phase of the desired signal is lost while measuring Fourier transform magnitude (F.T.M.). However, if a reference 'signal is added to the desired signal, then, in the Fourier trans form magnitude of the added signal, the Fourier transform phase of the desired signal is encoded. This paper addresses uniqueness and retrieval of the encoded Fourier phase of a multidimensional signal from the Fourier transform magnitude of the added signal along with the Fourier transform magnitude of the desired signal and the information of the additive reference signal. In Part I, several conditions under which the desired signal can be uniquely specified from the two Fourier transform magnitudes and the additive reference signal are presented. In Part II, the development of non-iterative algorithms and an iterative algorithm that may be used to reconstruct the desired signal(s) is considered.

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더해지는 기준신호를 이용한 위성복원: II. 복원 (Phase Retrieval Using an Additive Reference Signal: II. Reconstruction)

  • Woo Shik Kim
    • 전자공학회논문지B
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    • 제31B권5호
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    • pp.34-41
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    • 1994
  • Phase retrieval is concerned with the reconstruction of a signal from its Fourier transform magnitude (or intensity), which arises in many areas such as X-ray crystallography, optics, astronomy, or digital signal processing In such areas, the Fourier transform phase of the desired signal is lost while measuring Fourier transform magnitude (F.T.M.). However, if a reference 'signal is added to the desired signal, then, in the Fourier trans form magnitude of the added signal, the Fourier transform phase of the desired signal is encoded This paper addresses uniqueness and retrieval of the encoded Fourier phase of a multidimensional signal from the Fourier transform magnitude of the added signal along with Fourier transform magnitude of the desired signal and the information of the additive reference signal In Part I, several conditions under which the desired signal can be uniquely specified from the two Fourier transform magnitudes and the additive reference signal are presented In Part II, the development of non-iterative algorithms and an iterative algorithm that may be used to reconstruct the desired signal (s) is considered

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국부적 통계성을 이용한 웨이블렛 영역에서의 잡음 제거 (Denoising in the Wavelet Domain Using Local Statistics)

  • 임현;박순영
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 하계종합학술대회 논문집
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    • pp.1079-1082
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    • 1999
  • This paper presents a denoising algorithm that can suppress additive noise components while preserving signal components in the wavelet domain. The algorithm uses the local statistics of wavelet coefficients to attenuate noise components adaptively. Then threshohding operation is followed to reject the residuary noise components in the wavelet coefficients. Simulations are carried out over 1-D signals corrupted by Gaussian noise and the experimental results show the effectiveness of the proposed algorithm.

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EDGE를 보존하는 적응 영상 복원 (Adaptive Edge-preserving Image Restoration)

  • 김남철;이재덕
    • 대한전자공학회논문지
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    • 제23권5호
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    • pp.726-731
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    • 1986
  • An effective filtering algorithm which can reduce noise and preserve edges for the restoration of an image degraded by additive white Gaussian noise is presented. The algorithm proposed in this paper is an extension of Lee's algorithm modified to use local gradient information as well as local statistics. It does not require image modeling, and removes noise along the orientaiton of edges so that it does not blur the edge.

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AWGN 환경에서 화소 분포를 고려한 영상복원 알고리즘 (Image Restoration Algorithm Considering Pixel Distribution in AWGN Environments)

  • 권세익;김남호
    • 한국정보통신학회논문지
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    • 제19권7호
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    • pp.1687-1693
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    • 2015
  • 최근, 디지털 영상처리 장치에 대한 수요가 급격히 증대되면서 영상의 우수한 화질이 요구되고 있다. 그러나 디지털 영상을 획득, 처리, 전송하는 과정에서 여러 외부 원인에 의해 영상의 열화가 발생되고 잡음제거에 관한 연구가 대두되고 있다. 따라서 본 논문에서는 영상에 첨가되는 AWGN(additive white Gaussian noise)을 제거하기 위해, 3 × 3 마스크 내의 화소 분포에 따라 3개의 레벨로 나누어 처리하는 알고리즘을 제안하였다. 제안한 알고리즘은 AWGN (σ = 15)에 훼손된 Barbara 영상을 적용하여 처리한 결과, 기존의 MF(5 × 5), A-TMF(5 × 5), AWMF(5 × 5), MF (3 × 3), A-TMF(3 × 3), AWMF(3 × 3), GF(5 × 5)에 비해 각각 2.87[dB], 2.95[dB], 2.88[dB], 1.52[dB], 1.49[dB], 1.58[dB], 1.25[dB] 개선되었다.