• The Journal of the Korea Contents Association
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• v.3 no.2
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• pp.24-30
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• 2003

Pre-existing authentication system such as token based method, knowledge-based and hybrid method have problems such as loss and wiretapping. for this, this paper describes the biometric authentication system which have the excellent convenience and security. In particular, a new biometric system by human face biometric features which have the non-enforcement and non-touch measurement is proposed. Firstly, facial features are extracted by Y- histogram and tilted face images we corrected by coordinate transformation and scaling has done for achieving independent of the camera positions. Secondly, feature vectors are extracted such as distance and intersection angles and similarities we measured by fuzzy relation matrix. finally, the effectiveness of this paper is demonstrated by experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1517-1524
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• 2011

In this paper, a new document summarization method, which uses the semantic features and the pseudo relevance feedback (PRF) by using WordNet, is introduced to extract meaningful sentences relevant to a user query. The proposed method can improve the quality of document summaries because the inherent semantic of the documents are well reflected by the semantic feature from NMF. In addition, it uses the PRF by the semantic features and WordNet to reduce the semantic gap between the high level user's requirement and the low level vector representation. The experimental results demonstrate that the proposed method achieves better performance that the other methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.244-247
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• 1999

in this paper, we propose the recognition system of face using polynomial coefficients to recognize fact images using neural network. The system consists of following steps. First step, the sizes of fare images is reduced sizes of input images to 1/4 using wavelet transform. Second step, the polynomial coefficients is obtained from low frequency coefficient matrix after 3 level wavelet transform. Third step, polynomial coefficients is normalized. The of range of normalization is from -1 to 1. Last, Face images is trained and recognized using neural network with error back propagation algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.554-564
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• 2012

The vehicle recognition consists of two steps; the vehicle region detection step and the vehicle identification step based on the feature extracted from the detected region. Features using linear transformations have the effect of dimension reduction as well as represent statistical characteristics, and show the robustness in translation and rotation of objects. Among the linear transformations, the NMF(Non-negative Matrix Factorization) is one of part-based representation. Therefore, we can extract NMF features with sparsity and improve the vehicle recognition rate by the representation of local features of a car as a basis vector. In this paper, we propose a feature extraction using NMF suitable for the vehicle recognition, and verify the recognition rate with it. Also, we compared the vehicle recognition rate for the occluded area using the SNMF(sparse NMF) which has basis vectors with constraint and LVQ2 neural network. We showed that the feature through the proposed NMF is robust in the urban scene where occlusions are frequently occur.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.121-124
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• 1996

본 연구에서는 개선된 계층적 분석과정(AHP)을 사용하여 국산 신형 중형차의 우선 순위를 평가한다. AHP 모형은 외관, 성능, 안전성, 경제성, 영업사원, 사후정비의 주 기준과 39개 세부기준으로 구성된다. 구현의 특징을 (1) 샘플 크기가 작은 그룹의사결정 문제로 한정할 때, 한 의사결정자의 전체 쌍비교 행렬보다는 일관성비율이 한계치 이하의 행렬 만을 고려하였고, (2) 중요도 도출 과정에서 평가기준은 쌍비교 방식을, 대안은 레이팅 기법을 결합하였으며, (3) 그룹 중요도는 일관성 비율의 역수를 사용하였다. 사례 연구로 국내 자동차 판매 영업대표와 운전자를 대상으로 각각 평가기준에 대한 중요도와 레이팅 값을 도출, 3대 경쟁 차조의 우선순위를 비교 분석한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2603-2608
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• 2009

Document clustering is an important method for document analysis and is used in many different information retrieval applications. This paper proposes a new document clustering model using the clustering method based NMF(non-negative matrix factorization) and refinement of documents in cluster by using coherence of cluster. The proposed method can improve the quality of document clustering because the re-assigned documents in cluster by using coherence of cluster based similarity between documents, the semantic feature matrix and the semantic variable matrix, which is used in document clustering, can represent an inherent structure of document set more well. The experimental results demonstrate appling the proposed method to document clustering methods achieves better performance than documents clustering methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1599-1607
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• 2015

Recently, researches have been developing efficient techniques for accessing, querying, and managing XML documents which are frequently used in the Internet. In this paper, we propose a parent-child matrix to cluster XML documents efficiently. A parent-child matrix analyzes both the content and structural features of an XML document. Each cell of a parent-child matrix has either the value of a node in an XML tree or the value of a child node, where a parent-child relationship exists in the XML tree. Then, the similarity between two XML documents can be measured by the similarity between two corresponding parent-child matrices. The experiment shows that our proposed method has good performance.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.688-690
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• 2005

본 논문에서는 비디오 프레임에서의 특징점 추출과 3D 객체의 점들간의 상대적인 좌표만을 사용하여 비디오에 가상객 체를 삽입 하는 방법 을 제안한다. 가상객체의 삽입 위치는 사용자가 대응관계를 지정하여 결정한다. 3D 객체의 비디오 삽입을 위한 투사행렬은 POSIT 알고리즘을 사용하여 계산한다. 가상 객체를 삽입 함에 있어 실객체가 가상객체를 가리는 현상을 해결하였다. 본 논문에서 제안한 방법은 특징점과 3D 객체의 점들 간의 상대적인 좌표만 준비된다면 각 비디오프레임의 카메라 행렬을 계산할 수 있고 가상객체의 가려짐을 고려하여 합성할 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.648-654
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• 2009

In this paper, a method called bilateral diagonal 2DLDA is proposed for face recognition. Two methods called Dia2DPCA and Dia2DLDA were suggested to reserve the correlations between the variations in the rows and columns of diagonal images. However, these methods work in the row direction of these images. A row-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the column variation of alternative diagonal face images. In addition, column-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the row variation in diagonal images. A bilateral projection scheme was applied using left and right multiplying projection matrices. As a result, the dimension of the feature matrix and computation time can be reduced. Experiments carried out on an ORL face database show that the proposed method with three different distance measures, namely, Frobenius, Yang and AMD, is more accurate than some methods, such as 2DPCA, B2DPCA, 2DLDA, etc.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1178-1188
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• 2003

In this paper, we describe image mosaicing techniques for constructing a large high-resolution image with images taken by a video camera in hand. we propose the method which is automatically retrieving the exact matching area using color information and shape information. The proposed method extracts first candidate areas which have similar form using a Voronoi Distance Matching Method which is rapidly estimating the correspondent points between adjacent images, and calculating initial transformations of them and finds the final matching area using color information. It is a method that creates Voronoi Surface which set the distance value among feature points and other points on the basis of each feature point of a image, and extracts the correspondent points which minimize Voronoi Distance in matching area between an input image and a basic image using the binary search method. Using the Levenberg-Marquadt method we turn an initial transformation matrix to an optimal transformation matrix, and using this matrix combine a basic image with a input image.