• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2000년도 추계학술발표논문집 (상)
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• pp.751-754
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• 2000

In this paper, we propose an efficient method to detect abrupt shot changes in compressed MPEG video data by using reference ratios among video frames. The reference ratios among video frames imply the degree of similarities among adjacent frames by prediction coded type of each frames. A shot change is detected if the similarity degrees of a frame and its adjacent frames are low. This paper proposes an efficient shot change detection algorithm by using Fuzzy c-means(FCM) clustering algorithm. The FCM clustering uses the shot change probabilities evaluated in the mask matching of reference ratios and difference measure values based on frame reference ratios.

• 센서학회지
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• 제13권3호
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• pp.199-206
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• 2004

Epileptic seizures result from a temporary electrical disturbance of the brain. In this paper, a method of discriminating EEG for diagnoses of temporal lobe epilepsy is proposed. The proposed method for classification of epilepsy and sleep EEG is based on the wavelet transform and the fuzzy c-means. The magnitude and mean of wavelet coefficients for each EEG band are applied to the cluster of the FCM classifier. The proposed system show a little more accurate diagnosis for EEG by analysis of frequency for Wavelet and the success rate of 95% classification using FCM. From the simulation results by the implemented system, we demonstrated this research can be reduce doctor's labors and realize quantitative diagnosis of EEG.

• 전자공학회논문지B
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• 제32B권11호
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• pp.1536-1544
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• 1995

We propose a design scheme of a binary decision tree and apply it to the tire tread pattern recognition problem. In this scheme, a binary decision tree is constructed by using fuzzy C-means( FCM ) algorithm. All the available features are used while clustering. At each node, the best feature or feature subset among these available features is selected based on proposed similarity measure. The decision tree can be used for the classification of unknown patterns. The proposed design scheme is applied to the tire tread pattern recognition problem. The design procedure including feature extraction is described. Experimental results are given to show the usefulness of this scheme.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.173-179
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• 1998

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neural net, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Menas) arithmatics, to decide whether a requested call that is not trained in learning phase to be connected or not. The system generates the estimated traffic pattern of the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmatics. The input to the NN is the vector consisted of traffic parameters which is the means and variances of the number of cells arriving inthe interval. After training(using error back propagation algorithm), when the NN is used for decision making, the decision as to whether to accept or reject a new call depends on whether the output is greater or less then decision threshold(+0.5). This method is a new technique for call admi sion control using the membership values as traffic parameter which declared to CAC at the call set up stage, and is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simmulation. it is founded the performance of the suggested method outforms compared to the conventional NN method.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.217-222
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• 2009

In this paper, a new approach is proposed for the segmentation of Computed Tomography (CT) head images. The approach consists of two-stage segmentation with each stage contains two different segmentation techniques. The ultimate aim is to segment the CT head images into three classes which are abnormalities, cerebrospinal fluid (CSF) and brain matter. For the first stage segmentation, k-means and fuzzy c-means (FCM) segmentation are implemented in order to acquire the abnormalities. Whereas for the second stage segmentation, modified FCM with population-diameter independent (PDI) and expectation-maximization (EM) segmentation are adopted to obtain the CSF and brain matter. The experimental results have demonstrated that the proposed system is feasible and achieve satisfactory results.

• 한국멀티미디어학회논문지
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• 제13권1호
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• pp.47-57
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• 2010

객체 검출은 영상에서 객체의 식별, 위치정보, 상황인식 등을 위해서 필수적이다. 본 논문에서는 강인한 객체 검출 시스템을 제안한다. Principal Component Analysis (PCA)를 이용하여 배경 영상에서 수집한 학습데이터를 주성분으로 선형변환 한다. 객체와 배경에 대하여 판별 능력이 우수한 주성분을 선별하여 Eigen-background를 구성한다. Fuzzy-C-Means (FCM)은 Eigen-background의 정보를 입력 차원으로 하여 영상을 Clustering하고 객체와 배경으로 분류한다. 고정된 카메라에서 배경변화에 적용 가능한 시스템을 구현하기 위해 동일한 시점에서 움직이는 객체가 포함된 영상을 학습데이터로 사용하였다. 제안하는 시스템은 인위적인 한 프레임을 배경으로 정의하여 사용하는 과정이 필요 없이 입력 영상에서 잡음이 제거된 객체와 배경으로 분류하였고, 또한 객체의 부분적인 움직임도 효과적으로 검출하였다.

• Journal of information and communication convergence engineering
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• 제6권1호
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• pp.94-99
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• 2008

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy C-means clustering algorithm is employed to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

• Journal of information and communication convergence engineering
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• 제5권1호
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• 한국정보통신학회논문지
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• 제10권5호
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• pp.871-876
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• 2006

본 논문은 공간 부호화 패턴들을 이용하여 3차원 얼굴 정보를 정확하게 측정하기 위하여 초기 얼굴 패턴 영상으로부터 이미지 패턴을 검출하기 위한 새로운 알고리즘을 제안한다. 획득된 영상이 불균일하거나 패턴의 경계가 명확하지 않으면 패턴을 분할하기가 어렵다. 그리고 누적된 오류로 인하여 코드화가 되지 않는 영역이 발생한다. 본 논문에서는 이러한 요인에 강하고 코드화가 잘 될 수 있도록 FCM 클러스터링 방법을 이용하였다. 패턴 분할을 위하여 클러스터는 2개, 최대 반복횟수는 100, 임계값은 0.00001로 설정하여 실험하였다. 제안된 패턴 분할 방법은 기존 방법들(Otsu, uniform error, standard deviation, Rioter and Calvard, minimum error, Lloyd)에 비해 8-20%의 분할 효율을 향상시켰다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.109.6-109
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• 2002

In this paper, the scheme of fuzzy system construction using GA(genetic algorithm) and FCM(Fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. in the structure identification, input data is trans-formed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, the number of fuzzy rule is obtained by a given performance criterion. In the parameter identification, the premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this, one can systematically obtain optimal parameter and the v..