• Journal of Information Processing Systems
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• 제12권3호
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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.

• 반도체디스플레이기술학회지
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• 제18권4호
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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.

• 한국정보처리학회논문지
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• 제2권1호
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• pp.12-22
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• 1995

분산된 지역 데이타베이스의 스키마 통합시 중심 개념은 엔티티 통합을 의미하며 이때 엔티티의 시멘틱은 여러 요소에 영향을 받는다. 따라서 분산된 데이타베이스 환경에서의 스키마 통합은 통합되어야 하는 각 지역의 스키마의 엔티티 타입간의 도메 인 관계의 정의로부터 시작된다할 수 있다. 이렇게 설계자에 의해 정의되는 각 엔티티 간의 도메인 관계는 스키마 통합 시스템의 신뢰도의 확보와 검증을 위한 작업이 반드 시 수행되어야 한다. 그러나 이러한 작업이 기존의 통합 시스템에서는 제시되지 못하였다. 본 논문은 분산 시스템 환경에서 지역 데이타베이스의 스키마 통합을 위한 객체 중심의 통합을 정의하고, 통합의 타당성 검증을 위한 모델을 제안하고 검증 시 스템을 구현한다.

• 한국전자거래학회지
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• 제5권2호
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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 .

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 추계학술발표논문집 (하)
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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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• 제15권1호
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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.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 추계학술발표회 논문집
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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.

• 한국공간정보시스템학회 논문지
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• 제8권1호
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• pp.93-106
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• 2006

그리드 데이터베이스는 그리드 컴퓨팅 환경에서 분산된 데이터의 효율적 처리와 사용을 위한 데이터 베이스 관리 시스템이다. 공간 데이터는 일반적인 데이터에 비해 지역적 특성에 따른 이용도가 높으며, 대용량의 저장 공간을 필요로 하는 특징을 포함한다. 그리드 데이터베이스는 이러한 공간 데이터의 관리를 위한 최적의 시스템으로 적용 가능하다. 그러나, 기존의 분산 데이터베이스 시스템과는 달리 지역적 자율성을 보장하기 때문에 단일 관리자에 대한 적용이 불가능하거나 비효율적인 시스템 구성이 이루어질 가능성이 있다. 또한 동적으로 변화되는 환경에 유동적인 대응을 위해서는 효율적인 재조직 연산이 필요하다. 본 논문에서는 그리드 데이터베이스에서 계층 구조를 이용한 동적 재조직 기법을 제안한다. 제안 기법은 재조직 수행 시 데이터베이스들의 정보를 논리적으로 취합하는 오가나이저를 생성한다. 또한, 오가나이저를 계층적 구조로 구성을 함으로써 단계적인 정보 전파 및 재조직 연산 수행을 지원하게 된다. 이를 통해 지역적인 재조직 연산의 지원 및 효율적 균형 조정이 가능해진다. 부가적으로 불필요한 재조직 연산의 제거가 가능하다. 성능평가를 통해 제안 기법이 재조직 수행 후에 전체적인 처리량을 향상시킴을 보인다.

• Journal of Information Processing Systems
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• 제16권2호
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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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• 제8권5호
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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).