• 제목/요약/키워드: Skew Estimation

검색결과 39건 처리시간 0.02초

형태 모멘트를 이용한 텍스트 이미지 경사 측정 및 교정 (Skew Estimation and Correction in Text Images using Shape Moments)

  • Choo, Moon-Won;Chin, Seong-Ah
    • 한국콘텐츠학회논문지
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    • 제3권1호
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    • pp.14-20
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    • 2003
  • 문서 이미지 처리에서 텍스트 블록의 수평화 프로세스는 문서 인식 솔루션을 위한 전처리 단계로서 많은 연구가 진행되고 있다. 이 논문에서는 텍스트 이미지 블록의 직교각 속성과 형태 모멘트에 후프 변환을 적용하여 경사진 텍스트 블록을 원래 문서의 텍스트와 수평화된 텍스트 이미지로 변환하는 효율적인 방식을 제안한다. 실험을 통하여 제안된 방식의 비교 성능 결과를 보인다.

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Some counterexamples of a skew-normal distribution

  • Zhao, Jun;Lee, Sang Kyu;Kim, Hyoung-Moon
    • Communications for Statistical Applications and Methods
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    • 제26권6호
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    • pp.583-589
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    • 2019
  • Counterexamples of a skew-normal distribution are developed to improve our understanding of this distribution. Two examples on bivariate non-skew-normal distribution owning marginal skew-normal distributions are first provided. Sum of dependent skew-normal and normal variables does not follow a skew-normal distribution. Continuous bivariate density with discontinuous marginal density also exists in skew-normal distribution. An example presents that the range of possible correlations for bivariate skew-normal distribution is constrained in a relatively small set. For unified skew-normal variables, an example about converging in law are discussed. Convergence in distribution is involved in two separate examples for skew-normal variables. The point estimation problem, which is not a counterexample, is provided because of its importance in understanding the skew-normal distribution. These materials are useful for undergraduate and/or graduate teaching courses.

Bayesian Estimation for Skew Normal Distributions Using Data Augmentation

  • Kim Hea-Jung
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.323-333
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    • 2005
  • In this paper, we develop a MCMC method for estimating the skew normal distributions. The method utilizing the data augmentation technique gives a simple way of inferring the distribution where fully parametric frequentist approaches are not available for small to moderate sample cases. Necessary theories involved in the method and computation are provided. Two numerical examples are given to demonstrate the performance of the method.

MOMENTS OF VARIOGRAM ESTIMATOR FOR A GENERALIZED SKEW t DISTRIBUTION

  • KIM HYOUNG-MOON
    • Journal of the Korean Statistical Society
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    • 제34권2호
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    • pp.109-123
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    • 2005
  • Variogram estimation is an important step of spatial statistics since it determines the kriging weights. Matheron's variogram estimator can be written as a quadratic form of the observed data. In this paper, we extend a skew t distribution to a generalized skew t distribution and moments of the variogram estimator for a generalized skew t distribution are derived in closed forms. After calculating the correlation structure of the variogram estimator, variogram fitting by generalized least squares is discussed.

선택적 주의집중에 의한 문서영상의 효율적인 기울어짐 추정 (Efficient Skew Estimation for Document Images Based on Selective Attention)

  • 곽희규;김수형
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제26권10호
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    • pp.1193-1203
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    • 1999
  • 본 논문에서는 한글과 영문 문서 영상들에 대한 기울어짐 추정(skew estimation) 알고리즘을 제안한다. 제안 방법은 전체 문서 영상에서 텍스트 요소들이 밀집되어 있는 영역을 선별하고, 선별된 영역에 대해 허프 변환을 적용하는 선택적 주의집중(selective attention) 방식을 채택한다. 제안 방법의 기울기 추정 과정은 2단계로 구성되는데, coarse 단계에서는 전체 영상을 몇 개의 영역으로 나누고 동일한 영역에 속하는 데이타들간의 연결 각도를 계산하여 각 영역별 accumulator에 저장한다. accumulator에 저장된 빈도치를 기준으로 $\pm$45$^{\circ}$범위 내에서 최대 $\pm$1$^{\circ}$의 오차를 가진 각 영역별 기울기를 계산한 후, 이들 중 최대 빈도값을 갖는 영역을 선정하고 그 영역의 기울기 각도를 문서 영상의 대략적인 기울기 각도로 결정한다. Refine 단계에서는 coarse 단계에서 선정된 영역에 허프 변환을 적용하여 정확한 기울기를 계산하는데, coarse 단계에서 추정한 기울기의 $\pm$1$^{\circ}$범위 내에서 0.1$^{\circ}$간격으로 측정한다. 이와 같은 선택적 주의집중 방식을 통해 기울기 추정에 소요되는 시간 비용은 최소화하고, 추정의 정확도는 최대화 할 수 있다.제안 방법의 성능 평가를 위한 실험은 다양한 형태의 영문과 한글 문서 영상 2,016개에 적용되었다. 제안 방법의 평균 수행 시간은 Pentium 200MHz PC에서 0.19초이고 평균 오차는 $\pm$0.08$^{\circ}$이다. 또한 기존의 기울기 추정 방법과 제안 방법의 성능을 비교하여 제안 방법의 우수성을 입증하였다.Abstract In this paper we propose a skew estimation algorithm for English and Korean document images. The proposed method adopts a selective attention strategy, in which we choose a region of interest which contains a cluster of text components and then apply a Hough transform to this region. The skew estimation process consists of two steps. In the coarse step, we divide the entire image into several regions, and compute the skew angle of each region by accumulating the slopes of lines connecting any two components in the region. The skew angle is estimated within the range of $\pm$45 degree with a maximum error of $\pm$1 degree. Next we select a region which has the most frequent slope in the accumulators and determine the skew angle of the image roughly as the angle corresponding to the most frequent slope. In the refine step, a Hough transform is applied for the selected region within the range of $\pm$1 degree along the angle computed from the coarse step, with an angular resolution of 0.1 degree. Based on this selective attention strategy, we can minimize the time cost and maximize the accuracy of the skew estimation.We have measured the performance of the proposed method by an experiment with 2,016 images of various English and Korean documents. The average run time is 0.19 second on a Pentium 200MHz PC, and the average error is $\pm$0.08 degree. We also have proven the superiority of our algorithm by comparing the performance with that of other well-known methods in the literature.

ECM Algorithm for Fitting of Mixtures of Multivariate Skew t-Distribution

  • Kim, Seung-Gu
    • Communications for Statistical Applications and Methods
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    • 제19권5호
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    • pp.673-683
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    • 2012
  • Cabral et al. (2012) defined a mixture model of multivariate skew t-distributions(STMM), and proposed the use of an ECME algorithm (a variation of a standard EM algorithm) to fit the model. Their estimation by the ECME algorithm is closely related to the estimation of the degree of freedoms in the STMM. With the ECME, their purpose is to escape from the calculation of a conditional expectation that is not provided by a closed form; however, their estimates are quite unstable during the procedure of the ECME algorithm. In this paper, we provide a conditional expectation as a closed form so that it can be easily calculated; in addition, we propose to use the ECM algorithm in order to stably fit the STMM.

The skew-t censored regression model: parameter estimation via an EM-type algorithm

  • Lachos, Victor H.;Bazan, Jorge L.;Castro, Luis M.;Park, Jiwon
    • Communications for Statistical Applications and Methods
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    • 제29권3호
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    • pp.333-351
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    • 2022
  • The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and Student's-t distributions as special cases. In this work, we propose an EM-type algorithm for computing the maximum likelihood estimates for skew-t linear regression models with censored response. In contrast with previous proposals, this algorithm uses analytical expressions at the E-step, as opposed to Monte Carlo simulations. These expressions rely on formulas for the mean and variance of a truncated skew-t distribution, and can be computed using the R library MomTrunc. The standard errors, the prediction of unobserved values of the response and the log-likelihood function are obtained as a by-product. The proposed methodology is illustrated through the analyses of simulated and a real data application on Letter-Name Fluency test in Peruvian students.

Reliability In a Half-Triangle Distribution and a Skew-Symmetric Distribution

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권2호
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    • pp.543-552
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    • 2007
  • We consider estimation of the right-tail probability in a half-triangle distribution, and also consider inference on reliability, and derive the k-th moment of ratio of two independent half-triangle distributions with different supports. As we define a skew-symmetric random variable from a symmetric triangle distribution about origin, we derive its k-th moment.

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가중회귀분석에 의한 지역화왜곡계수의 추정 (Estimation of Regionai Skew Coefficient with Weighted Least Squares Regression)

  • 조국광;권순국
    • 한국농공학회지
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    • 제32권1호
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    • pp.103-109
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    • 1990
  • The application of the Log-Pearson Type m distribution recommended by Water Resources Council, U. S. A. for flood frequency analysis requires the estimation of the regionalized skew coefficient. In this study, regionalized skew coefficients are estimated using a weighted regression model which relates at-site skews based on logarithms of observed annual flood peak series to both basin characteristics and precipitation data in the Han river and the Nakdong river basin. The model is developed with weighted least squares method in which the weights are determined by separating residual variance into that due to model error and due to sampling error. As the result of analysis, regionalized skews are estimated as - 0.732 and - 0.575 in the Han river and the Nakdong river basin, respectively.

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무선 센서네트워크에서의 시각동기를 위한 실시간 클럭 스큐 추정 (Realtime Clock Skew Estimator for Time Synchronization in Wireless Sensor Networks of WUSB and WBAN)

  • 허경
    • 한국멀티미디어학회논문지
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    • 제15권11호
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    • pp.1391-1398
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    • 2012
  • 무선 센서네트워크에서의 시각동기는 Wireless USB, WBAN 등의 MAC 계층에서부터 응용 계층에 이르기까지 거의 모든 계층에서 다양한 목적을 위해 매우 중요한 기술이다. 본 논문에서는 무선 센서네트워크에서의 시각동기를 위한 실시간 클럭 스큐 추정 방법을 제시한다. 재귀적 최소제곱법을 통해 오프셋 보정 정보들을 얻을 때마다 클럭 스큐가 실시간적으로 추정 및 갱신되며, 아울러 스큐 추정을 위해 각 센서노드에 저장해야할 정보를 최소화한다. 제안한 클럭 스큐 추정 방법은 기존의 클럭 오프셋 보정 방법과 쉽게 통합될 수 있으며, 이 경우 보다 정확하고 효율적인 시각동기화가 가능해진다. 시뮬레이션 및 실험 결과를 통해 제안한 클럭 스큐 추정 방법을 통한 시각동기 정확도의 향상을 보인다.