• Journal of Information Processing Systems
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• v.12 no.3
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• pp.468-488
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• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.57-61
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• 2019

Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.12-22
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• 1995

When we integrate schema of distributed local databases, we mean entity integration as central concept of schema integration, and semantic of entity affects several factors. Thus the schema integration in distributed database environment starts from definition of domain relation among entity types of local schemas. Moreover, the domain relation defined by designer needs some works for confidence and validation of schema integration system. But this work was not presented in previous integration system. In this paper, we define object oriented integration for schema integration of local databases in distributed system environment, present models to verify validation on its integration, and implement the validation system.

• The Journal of Society for e-Business Studies
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• v.5 no.2
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• pp.61-79
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• 2000

For CALS environment, sharing information among business processes within the enterprise and between enterprises have been increased through common database. To support integrated data environment, data of the local legacy system must coincide with data of the global system to guarantee data integrity and transparency. This study is concerned with the implementation of this distributed database system under CALS environment. Based on existing IDEF methods, we developed a modified method which newly includes concepts of the enterprise structure, the integration of legacy databases, the distribution of data, and the distributed applications .

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1449-1452
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• 2003

국내에서 지방자치단체의 정보화 추진은 정보화의 변화 추세에 따라 업무별로 자료를 구축하여 활용되고 있으나 통합적으로 연결된 형태의 자료구축이 이루어지지 않고 있어 현 정보시스템의 활용 효율을 높이고 의사결정지원을 위한 정보시스템의 구축이 필요하다. 이에 지방자치단체에서 업무적으로 연결된 통합 DB(Database)와 DW(Data Warehouse)를 구축하여 업무 편리성을 높이고 의사결정에 활용할 수 있는 모델을 제시한다.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.325-333
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• 2004

Since 1995, One of the NGIS(National Geographic Information System) projects, the underground utilities project has been finished in 2003. The 19 cities in korea for this project will use underground utilities management system using underground utilities database focusing on water and sewage system. However, special expert, technical and experience problem in computer environment has not been had in working department for water and sewage management and maintenance for each local government. The management and maintenance of underground utilities database by manual method is getting lowered a data quality of underground utilities database because of the data omitting, error in writing and securing of the lasted database. Therefore, in this study, Application test for field workers using a mobile tool and environment analysis of wireless communication in Korea and application test of GPS receiver for mobile tools had been processed and made a mobile working environment. The efficient management and maintenance method for underground utilities database has been developed an off- line method for modification and update of database about general work which has a high working frequency because of the limitation of wireless communication environment Also, the emergency working has been applied for on-line method.

• Journal of Korea Spatial Information System Society
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• v.8 no.1 s.16
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• pp.93-106
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• 2006

A Grid Database is a database management system to process effectively and use the distributed data in a grid computing environment. Spatial data is more important than other general data according to the local characteristics and requires a large storage. The grid database can be used as the optimal system for the management of the spatial data. However, contrary to the conventional distributed database systems, the Grid Database which guarantees the local autonomy has a possibility not to provide an effective system, or it is impossible to use a centralized management environment. In order to allow flexible responses to a dynamically changing environment, it is required to use effectively reorganized method. In this paper, hierarchical reorganization method is presented for dynamic reorganization in a grid database. When the reorganization is conducted, an organizer is created to collect the information of databases. In addition, the organizer which is constructed by the hierarchical structure supports information communication and reorganization, and then it allows the support of regional reorganization operation and effective balance control. The performance assessment of the proposed method shows that the processing capacity is increased after the reorganization.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.343-359
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• 2020

In this paper, a new algorithm is proposed for three-dimensional (3D) shape recognition using local features of model views and its sparse representation. The algorithm starts with the normalization of 3D models and the extraction of 2D views from uniformly distributed viewpoints. Consequently, the 2D views are stacked over each other to from view cubes. The algorithm employs the descriptors of 3D local features in the view cubes after applying Gabor filters in various directions as the initial features for 3D shape recognition. In the training stage, we store some 3D local features to build the prototype dictionary of local features. To extract an intermediate feature vector, we measure the similarity between the local descriptors of a shape model and the local features of the prototype dictionary. We represent the intermediate feature vectors of 3D models in the sparse domain to obtain the final descriptors of the models. Finally, support vector machine classifiers are used to recognize the 3D models. Experimental results using the Princeton Shape Benchmark database showed the average recognition rate of 89.7% using 20 views. We compared the proposed approach with state-of-the-art approaches and the results showed the effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1766-1784
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• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).