• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.643-646
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• 1999

In this paper, we propose a feature extraction method based on Bhattacharyya distance for multiclass problems. The Bhattacharyya distance provides a valuable information in determining the effectiveness of a feature set and has been used as separability measure for feature selection. Recently, a feature extraction algorithm hat been proposed for two normally distributed classes based on Bhattacharyya distance. In this paper, we propose to expand the previous approach to multiclass cases. Experiment results show that the proposed method compares favorably with the conventional methods.

• 대한전자공학회논문지SP
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• 제37권6호
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• pp.38-47
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• 2000

Bhattacharyya distance는 패턴 분류 문제에 있어서 클래스간 분리도 측정의 수단으로 사용되어 왔으며 특징 추출 시 유용한 정보를 제공한다. 본 논문에서는 최근 발표된 Bhattacharyya distance를 이용한 에러 예측 기법을 이용하여 예측된 분류 에러가 최소가 되는 특정 벡터를 추출하는 방법에 대하여 제안한다. 제안한 특징 추출 기법은 최적화 알고리즘인 전체탐색 및 순차탐색 방법의 적용 시 분류 에러를 직접 구하지 않고 Bhattacharyya distance를 이용하여 분류 에러를 예측하므로 고차원 데이터의 경우 고속의 특징 추출이 가능하며, 에러 예측 성질을 이용하여 패턴 분류 시 필요한 최소 특징 벡터의 수를 예측할 수 있는 장점이 있다.

• Journal of the Optical Society of Korea
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• 제15권4호
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• pp.357-361
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• 2011

Photon-counting sensing is a widely used technique for low-light-level imaging applications. This paper proposes a distance information extraction method with photon-counting passive sensing under low-lightlevel conditions. The photo-counting passive sensing combined with integral imaging generates a photon-limited elemental image array. Maximum-likelihood estimation (MLE) is used to reconstruct the photon-limited image at certain depth levels. The distance information is extracted at the depth level that minimizes the sum of the standard deviation of the corresponding photo-events in the elemental image array. Experimental and simulation results confirm that the proposed method can extract the distance information of the object under low-light-level conditions.

• Journal of the Optical Society of Korea
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• 제20권5호
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• pp.579-585
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• 2016

Integral imaging combined with photon-counting detection has been researched for three-dimensional information sensing under low-light-level conditions. This paper addresses the extraction of distance information with photon-counting integral imaging. The longitudinal distance to the object is obtained utilizing photon-counting elemental images. The pixel disparity is estimated by maximizing the nonlinear correlation of photocounts. The first- and second-order statistical properties of the nonlinear correlation are theoretically derived. In the experiments, these properties are verified by varying the mean number of photocounts in the scene. The average distance is compared to that from the intensity information, showing the robustness of the proposed system even at low photocounts.

• 대한치과교정학회지
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• 제21권1호
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• pp.223-238
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• 1991

This study was carried out in order to findout the amount of tooth movement, the changes arch size and the changes in arch morphology following orthodontic treatment and to provide a guideline for to predict post-treatment arch morphology. The sample group for this study consists of 15 males and 22 females, totalling in 37 persons, who received orthodontic treatment at Orthodontic Department of Dankook Univ. Dental Hospital. They are classified into Extraction Class I treatment group (E I), Non-extraction Class I treatment group (N I), and Non-extraction Class III treatment group (N III), according to their pre-treatment malocclusion state and methods of treatment. Following conclusions and averaged dental arch form for each group were obtained by cephalometric linear measurements and dental arch measurements using pre- and post-treatment lateral cephalograms and plaster study models. 1. Intercanine width were reduced in max. of both EI and NI during the period of treatment, 2. Intermolar width were reduced in max. of EI and increased in max. of NI. Therefore although there was no difference between these two groups before the treatment, intermolar width of the max, of NI was wider than that of E1 after the treatment. 3. PMV-incisor distance and PMV-canine distance were decreased in both max. and mand. of EI and that of NI, during the period of treatment. PMV-molar distance was decreased in both max. and mand. of NI and in mand. of NIII. 4. Items that showed stability during the treatment were: max. & mand. PMV-molar distance, mand. intercanine and intermolar width in EI; mand. intercanine and intermolar width in NI; mand. & max. PMV-incisor distance, PMV-canine distance, max. PMV-molar distance and max. & mand. intercanine and intermolar width in NIII. 5. The differences in averaged canine and molar variances to post-treatment dental arch form were present only in EI and in NI. There was no variance between maxilla and mandible in each group.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2470-2491
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• 2018

Web-scale open information extraction (Open IE) plays an important role in NLP tasks like acquiring common-sense knowledge, learning selectional preferences and automatic text understanding. A large number of Open IE approaches have been proposed in the last decade, and the majority of these approaches are based on supervised learning or dependency parsing. In this paper, we present a novel method for web scale open information extraction, which employs cosine distance based on Google word vector as the confidence score of the extraction. The proposed method is a purely unsupervised learning algorithm without requiring any hand-labeled training data or dependency parse features. We also present the mathematically rigorous proof for the new method with Bayes Inference and Artificial Neural Network theory. It turns out that the proposed algorithm is equivalent to Maximum Likelihood Estimation of the joint probability distribution over the elements of the candidate extraction. The proof itself also theoretically suggests a typical usage of word vector for other NLP tasks. Experiments show that the distance-based method leads to further improvements over the newly presented Open IE systems on three benchmark datasets, in terms of effectiveness and efficiency.

• 스마트미디어저널
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• 제2권1호
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• pp.31-36
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• 2013

A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.

• 한국안전학회지
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• 제26권5호
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• pp.17-22
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• 2011

This study proposes feature extraction method of pattern recognition by evaluation of weld defects in weld zone of titanium. For this purpose, analysis objectives in this study are features of attractor quadrant and fractal dimension. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics resulting from distance shifts such as porosity of weld zone. These differences in characteristics of weld defects enables the evaluation of unique characteristics of defects in the weld zone. In quantitative fractal feature extraction, feature values of 0.87 and 1.00 in the case of part of 0.5 skip distance and 0.72 and 0.93 in the case of part of 1.0 skip distance were proposed on the basis of fractal dimensions. Attractor quadrant point, feature values of 1.322 and 1.172 in the case of ${\phi}1{\times}3mm$ porosity and 2.264 and 307 in the case of ${\phi}3{\times}3mm$ porosity were proposed on the basis of distribution value. The Proposed feature extraction of pattern recognition in this study can be used for safety evaluation of weld zone in titanium.

• 한국멀티미디어학회논문지
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• 제5권3호
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• pp.272-280
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• 2002

본 논문은 스테레오 비젼 시스템을 이용하여 이동 객체를 추출하고 그 객체까지의 거리를 측정하는 방법을 제안하였다. 이동 객체에 대한 이동 성분은 화소 단위의 정합을 통하여 추출하였으며, 적응형 임계값은 영상의 밝기 변화를 제거하는데 효과적으로 대처할 수 있었다. 이동 객체까지의 거리는 평행식 카메라를 적용한 스테레오 비전 시스템을 사용하여 측정하였다. 실험 결과 이동 객체에 대한 거리측정 오차가 평균 1%로 나타남으로써 제안한 알고리즘을 이용한 이동 객체의 거리측정 가능성을 제시하였다.

• 한국정밀공학회지
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• 제19권11호
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• pp.103-111
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• 2002

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.