• 대한의용생체공학회:의공학회지
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• 제28권5호
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.

• 복식
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• 제58권6호
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• pp.35-41
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• 2008

The purposes of this study lied in the analysis and classification of neck-base circumference shapes of the women in their twenties, by the application of three-dimensional automatic measurement data of human body, and thereby in the understanding of neck-base circumference shapes by the classified type. The findings are as follows: 1. The comparison of three-dimensional human body measurement items relating to the neck-base circumference part of the women in their twenties indicated that the largest individual difference was found in cervicale-center-anterior neck radius than in other items. 2. The factor analysis, which was conducted to extract the factors constituting the neck-base circumference, showed the shape of cervicale(factor 1), the shape of section neck(factor 2), the thickness of neck(factor 3), the shape of anterior neck(factor 4), and the shape of side neck(factor 5). 3. The classification of the neck-base circumference shapes resulted in three types. Type 1 was the shape of a reverse triangle hanging forward, Type 2 was that of a circle, and Type 3 was that of an oval open to the sides.

• 전자공학회논문지CI
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• 제43권5호
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• pp.38-47
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• 2006

기존의 인식 방법은 물체에 대한 형상 정보 또는 움직임을 특징으로 한 단일 인식기를 사용한다. 하지만, 기존의 단일 특징 기반의 단일 인식기를 사용하는 방법의 인식 성능은 물체의 영역에 대한 정확한 검출에 크게 의존하는 단점을 가진다. 본 논문에서는 이러한 기존 인식방법의 단점을 해결하고, 인식의 신뢰성을 높이기 위해서 세 가지 인식기에 의한 각 결과를 Bayesian을 이용하여 융합하는 새로운 인식 방법을 제안한다. 첫 번째 인식기는 푸리에 묘사자로부터 얻은 형상 정보를 특징으로 한 신경망을 사용하고, 두 번째 인식기는 형상 정보에 대한 기울기를 바탕으로 한 통계적인 방법을 사용한다. 또한. 세 번째 인식기는 검출된 물체의 일정 부분의 움직임에 대한 모션 정보를 특징으로 하여 인식한다. 본 논문의 실험결과에서 제안한 결과 융합방법은 기존의 Majority Voting과 Weight Average Score 방법에 비해서 더 우수한 인식 성능을 보여준다.

• 한국정보과학회논문지:데이타베이스
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• 제30권4호
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• pp.362-371
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• 2003

이 논문에서는 이미지 데이타베이스에서 모양 특징 기반 이미지 분류와 인덱싱을 위해 객체의 윤곽선 특성을 고려해 임계값을 동적으로 결정하여 최적 우세점을 추출하는 알고리즘을 제안한다. 동적 임계값결정은 원본 모양의 윤곽선 길이 비와 근사화된 다각형의 둘레 길이 비를 알고리즘 수행시 점진적으로 검사하는 방법을 사용한다. 이 알고리즘은 윤곽선 특징을 반영하여 동적인 임계값 검사를 함으로써 의사점 수를 최대한 줄이며 최소 우세점만으로 모양 특징 정보를 추출할 수 있는 장점을 보인다. 제안한 방법은 객체의 윤곽선을 이루는 n개의 점에서 m개의 최적 우세점을 찾는데 평균 O(nlogn)이 걸린다. 최적화 평가는 7가지 서로 다른 특성을 가지는 70개의 합성 모양과 1,100개의 어류 모양에 대해 알고리즘을 적용하고 피 결과에 대해 평가 함수를 구성하여 수행하였다. 최적화율은 실험 모양들에 대해 평균0.92를 보였으며 기존 알고리즘에 대해 약 14% 최적화 성능 개선을 보였다. 제안한 알고리즘을 통해 추출한 모양 특징 정보는 정규화를 통해 이미지 분류와 인덱싱, 유사도 검색에 활용할 수 있다.

• 전자공학회논문지B
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• 제31B권4호
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• pp.1-8
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• 1994

In this paper, we propose an efficient two-step pattern matching method which promises shape distortion-tolerant recognition of handwritten of handwritten Hangul syllables. In the first step, nonlinear shape normalization is carried out to compensate for global shape distortions in handwritten characters, then a preliminary classification based on simple pattern matching is performed. In the next step, nonlinear pattern matching which achieves best matching between input and reference pattern is carried out to compensate for local shape distortions, then detailed classification which determines the final result of classification is performed. As the performance of recognition systems based on pattern matching methods is greatly effected by the quality of reference patterns. we construct reference patterns by combining the proposed nonlinear pattern matching method with a well-known averaging techniques. Experimental results reveal that recognition performance is greatly improved by the proposed two-step pattern matching method and the reference pattern construction scheme.

• Communications for Statistical Applications and Methods
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• 제31권3호
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• pp.309-322
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• 2024

Identifying algae in water is important for managing algal blooms which have great impact on drinking water supply systems. There have been various microscopic approaches developed for algae classification. Many of them are based on the morphological features of algae. However, there have seldom been mathematical frameworks for comparing the shape of algae, represented as a planar continuous curve obtained from an image. In this work, we describe a recent framework for computing shape distance between two different algae based on the elastic metric and a novel functional representation called the square root velocity function (SRVF). We further introduce statistical procedures for multiple shapes of algae including computing the sample mean, the sample covariance, and performing the principal component analysis (PCA). Based on the shape distance, we classify six algal species in watersheds experiencing algal blooms, including three cyanobacteria (Microcystis, Oscillatoria, and Anabaena), two diatoms (Fragilaria and Synedra), and one green algae (Pediastrum). We provide and compare the classification performance of various distance-based and model-based methods. We additionally compare elastic shape distance to non-elastic distance using the nearest neighbor classifiers.

• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.543-549
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• 2008

Inspired by using a robust loss function in the support vector machine regression to control training error and the idea of robust template matching with M-estimator, Chen (2004) applies M-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for the support vector machines. We are specially interested in the shape of the Huber's M-estimator in this context and propose a way to find the shape parameter of the Huber's M-estimating function. For simplicity, only the two-class classification problem is considered.

• 한국멀티미디어학회논문지
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• 제13권8호
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• pp.1115-1127
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• 2010

TFT-LCD 생산 과정에서 발생하는 결함을 정확하게 분류하여 결함 유형에 따라 폐기, 사용가능 등의 의사결정을 적절하게 내리는 것은 수율 증가 및 생산성 향상에 필수적인 요소이다. 본 논문에서는 TFT-LCD 생산 라인에서 획득한 결함 영상에 대하여 명암도 분포(intensity distribution) 및 결함 영상의 형태 특징(shape feature)을 분석하여 효과적으로 필름 결함 유형을 분류하는 기법을 제시한다. 본 연구에서는 먼저 필름 결함 영상을 결함 영역과 결함이 아닌 배경 영역으로 이진화하고, 결함 영역에서 결함의 선형성(linearity), 명암도 분포를 고려한 형태 특징 등의 여러 가지 특징을 분석하여 기준 영상(referential image) 데이터베이스를 구축하였으며, 분류하고자 하는 결함 영상과 데이터베이스에 저장된 기준 영상과의 매칭 비용 함수(matching cost function)를 정의하여 적절히 매칭시킴으로써 결함의 유형을 결정하였다. 제시한 기법의 성능을 검증하기 위하여 실제 TFT-LCD 생산 라인에서 획득한 결함 영상들을 대상으로 분류 실험을 수행하였으며, 실험 결과 생산 라인에서 이용할 수 있을 정도의 상당한 수준의 분류 정확도를 달성하였음을 보여주었다.

• 한국의류학회지
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• 제26권7호
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• pp.1026-1035
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• 2002

The purposes of this study were to classify the front view of trunk of adult males into several kinds of shape and to provide the characteristics and silhouette of each group which has same shape. As the sample, subjects were l290 males of 20 to 54 year-old. The procedure and results were follows; l. The principal component analysis was used to obtain the shape factor of the front of the trunk 8 factors in the front which explained 86.8% of total variance were extracted. 2. As the result of the cluster analysis of factor scores, the font of body was classified in 4 types. 4 types were named X, A, Y and H type in the front considering the characteristics of each type.

• 복식문화연구
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• 제13권3호
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• pp.344-360
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• 2005

The purpose of the study is to identify the physical characteristics of early adolescent boys, to classify body shapes by physical characteristic. The subjects were 549 boys in the capital area. Their body shapes were identified and classified based on 47 anthropometric measurements, 43 photographic measurements and 10 indexed measurements. For data analysis were performed descriptive statistics, factor analysis, cluster analysis, ANOVA and Duncan test using SPSS Ver. 10. According to the result of extracting factors indicating the characteristics of body shape, horizontal size, vertical length, lateral posture, the lateral shape of the abdomen and the hip, the shape of the back protrusion, the front shape of the trunk and was the shape of the shoulders. According to the result of classifying body shapes, four types of shape - T(Tall) type, P(Petite) type, L(Large) type and R(Regular) type were identified. The results of this study are expected to contribute to planning sizes according to the type of body shape and improving the fitness of ready-made clothes in apparel and school uniform manufacturers.