• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.315-318
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• 2007

자동 얼굴 인식, 표정 인식과 같은 얼굴 영상과 관련된 다양한 연구 분야는 일반적으로 입력 얼굴 영상에 대한 정규화가 필요하다. 사람의 얼굴은 표정, 조명 등에 따라 다양한 형태변화가 있어 입력 영상 마다 정확한 대표 특징 점을 찾는 것은 어려운 문제이다. 특히 감고 있는 눈이나 작은 눈 등은 검출하기 어렵기 때문에 얼굴 관련 연구에서 성능을 저하시키는 주요한 원인이 되고 있다. 이에 다양한 변화에 강건한 눈 검출을 위하여 본 논문에서는 눈의 텍스처 정보를 이용한 눈 검출 방법을 제안한다. 얼굴 영역에서 눈의 텍스처가 갖는 특성을 정의하고 두 가지 형태의 Eye 필터를 정의하였다. 제안된 방법은 Adaboost 기반의 얼굴 영역 검출 단계, 조명 정규화 단계, Eye 필터를 이용한 눈 후보 영역 검출 단계, 눈 위치 점 검출 단계 등 총 4단계로 구성된다. 실험 결과들은 제안된 방법이 얼굴의 자세, 표정, 조명 상태 등에 강건한 검출 결과를 보여주며 감은 눈 영상에서도 강건한 결과를 보여준다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제14권1호
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• pp.9-16
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• 1996

A new stereo matching method for the relative orientation and the photogrammetric triangulation has been pro-posed. It matches the pairs of conjugate points to be used as pass points and tie points in digital aerial photographs instead of selecting these points with manual point transfer and measurements. Three unique steps included in the proposed matching method are as followings. The first step is searching interest points, and designating them as candidate points to be matched. The second is matching the points from the pair of images by the Cross Correlation Method in both direction(left to right direction and right to left). The third is selecting consistent pairs in the both matching directions. Computer programs based on the proposed matching method have been developed, and with digital aerial photographs which have full ground coordinate information tests were performed to know reliabiliy and positional accuracy of proposed method. Results of the tests reveal that the proposed matching method can eliminate the in-correctly matched pairs more efficiently than other matching methods, thus this can be more reliably applied to the relative orientation and the photogrammetric triangulation.

• Journal of Korea Spatial Information System Society
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• 제11권3호
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• pp.55-62
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• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

• Journal of Internet Computing and Services
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• 제10권5호
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• pp.65-78
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• 2009

The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.

• Journal of the Institute of Electronics and Information Engineers
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• 제49권9호
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• pp.113-127
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• 2012

Face detection methods using image processing have been proposed in many different ways. Generally, the most widely used method for face detection is an Adaboost that is proposed by Viola and Jones. This method uses Haar-like feature for image learning, and the detection performance depends on the learned images. It is well performed to detect face images within a certain distance range, but if the image is far away from the camera, face images become so small that may not detect them with the pre-learned Haar-like feature of the face image. In this paper, we propose the far distance face detection method that combine the Aadaboost of Viola-Jones with a saliency map and user's attention information. Saliency Map is used to select the candidate face images in the input image, face images are finally detected among the candidated regions using the Adaboost with Haar-like feature learned in advance. And the user's eye-tracking information is used to select the interest regions. When a subject is so far away from the camera that it is difficult to detect the face image, we expand the small eye gaze spot region using linear interpolation method and reuse that as input image and can increase the face image detection performance. We confirmed the proposed model has better results than the conventional Adaboost in terms of face image detection performance and computational time.

• Journal of Korea Multimedia Society
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• 제6권7호
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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.

• Journal of the Korea Society of Computer and Information
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• 제13권6호
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• pp.243-251
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• 2008

This study is to suggest the extraction algorithms of fingerprint corepoint and region separation using the labeling for gate security in order that it might be applied to the fingerprint recognition effectively. The gate security technology is entrance control, attendance management, computer security, electronic commerce authentication, information protection and so on. This study is to extract the directional image by dividing the original image in $128{\times}128$ size into the size of $4{\times}4$ pixel. This study is to separate the region of directional smoothing image extracted by each directional by using the labeling, and extract the block that appeared more than three sorts of change in different directions to the corepoint. This researcher is to increase the recognition rate and matching rate by extracting the corepoint through the separation of region by direction using the maximum direction and labeling, not search the zone of feasibility of corepoint or candidate region of corepoint used in the existing method. According to the result of experimenting with 300 fingerprints, the poincare index method is 94.05%, the proposed method is 97.11%.

• Journal of the Korea Society of Computer and Information
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• 제10권4호
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• pp.203-211
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• 2005

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps; preprocessing, classification, and matching, in the classification. we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Korean journal of communication and information
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• 제32권
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• pp.113-146
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• 2006

This study explored how media and interpersonal communication affected voters in Busan mayoral by-election, focusing on the mutual relations among media use and attentive use of political campaign, interpersonal communication, and voting participation. Also, comparative analysis between image factor and the factor of political party influencing the decision of a candidate were examined. Additionally, it was analysed differential media effects on candidates' image. According to the results, the local media use and attentive use of political campaign had the influence on the increase of interpersonal communication about the election. Voters who had much interpersonal discussion with others participated more than voters who had less interpersonal discussion. Media use did not directly affect the participation of voting, but indirectly contributed to participation of voting through interpersonal discussion. The assumption of differential media effects on candidates image was partly proved. There were statistically significant differences in the factor of competence of candidates' image among three experimental groups (attentive use of TV discussion program, Internet web sites of two candidates, and printing materials of political advertisement). Furthermore, with three main vote variables, issues, candidates image, party identification, the results of comparative analysis between image factor and the factor of political party influencing the choice of a candidate suggested that a sense of oneness with a party was highly related to the choice of the candidates of the party, however, candidates' image was not related to the decision of a candidate. Political party had more impact on for whom to vote than candidates' image in this study.

• Journal of the Korean Association of Geographic Information Studies
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• 제14권2호
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• pp.53-68
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• 2011

A selection of viewpoint is a first priority for landscape evaluation. However, it has been artificially carried out by a subjective method without of criterion. Therefore, this study proposed the objective and quantitative viewpoint selection methods using space syntax and GIS. For this, the study area on samduk3 residential improvement district located at Daegu city was divided into 24 sectors of visibility zone by distance and direction. After that, the preliminary viewpoints equally distributed in space were selected by axial map analysis of space syntax and viewshed-frequency analysis of GIS. According to the result of selection of the final viewpoints using the VEI(Viewpoint Evaluation Index), all the final viewpoints were placed in the National Debt Repayment Movement; VEI value of VP-2 was 112.63 in the foreground, VP-10 was 18.31 in the middleground and VP-18 was 5.55 in the background. Selected viewpoints were verified as a big changing of landscape variation and high chance of view such as the public area, the park and the high-density residential area. Thus, VEI will be used as a quantitative method of selecting viewpoints and it is expected to be able to use as the objective indicator.