• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.429-436
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• 2010

This paper presents a method to extract 3D outlines of objects in an image obtained from a monocular vision. After detecting the general outlines of the object by MOPS(Multi-Scale Oriented Patches) -algorithm and we obtain their spatial coordinates. Simultaneously, it obtains the space-coordinates with feature points to be immanent within the outlines of objects through SIFT(Scale Invariant Feature Transform)-algorithm. It grasps a form of objects to join the space-coordinates of outlines and SIFT feature points. The method which is proposed in this paper, it forms general outlines of objects, so that it enables a rapid calculation, and also it has the advantage capable of collecting a detailed data because it supplies the internal-data of outlines through SIFT feature points.

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.1-15
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• 2007

Traceability links are logical links between individual requirements and other system elements such as architecture descriptions, source code, and test cases. These are useful for requirements change impact analysis, requirements conflict analysis, and requirements consistency checking. However, establishing and maintaining traceability links places a big burden since complex systems have especially yield an enormous number of various artifacts. We propose a feature-oriented requirements tracing method to manage requirements with cost benefit analysis, including value consideration and intermediate catalysis using features. Our approach offers two contributions to the study of requirements tracing: (1)We introduce feature modeling as intermediate catalysis to generate traceability links between user requirements and implementation artifacts. (2)We provide value consideration with cost and efforts to identify traceability links based on prioritized requirements, thus assigning a granularity level to each feature. In this paper, we especially present the results of a case study which is carried out in Apartment Ubiquitous Platform to integrate and connect home services in an apartment complex in details.

• 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).

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.

• International Journal of Contents
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• v.9 no.3
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• pp.1-9
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• 2013

In this paper, we propose a fast and accurate system for detecting pedestrians from a static image. Histogram of Oriented Gradients (HOG) is a well-known feature for pedestrian detection systems but extracting HOG is expensive due to its high dimensional vector. It will cause long processing time and large memory consumption in case of making a pedestrian detection system on high resolution image or video. In order to deal with this problem, we use Principal Components Analysis (PCA) technique to reduce the dimensionality of HOG. The output of PCA will be input for a linear SVM classifier for learning and testing. The experiment results showed that our proposed method reduces processing time but still maintains the similar detection rate. We got twenty five times faster than original HOG feature.

• Asia pacific journal of information systems
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• v.10 no.1
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• pp.81-106
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• 2000

Recently there have been many efforts to develop hypermedia systems. Hypermedia applications can be categorized into process-oriented or contents-oriented. However, it is not a trivial task to build contents-oriented hypermedia in a systematic fashion. The contents-oriented hypermedia systems are developed primarily for the applications of marketing or information services. This paper proposes a methodology for a contents-oriented hypermedia system. Hypermedia contents are typically structured in the form of hierarchies. An index node can be used in order to give an effective access to this hierarchical structure. The proposed methodology employs three types of nodes(contents, index and function) and various navigation mechanisms, and helps design contents-oriented hypermedia systematically. Furthermore, various design techniques are proposed for maintaining contents-oriented hypermedia systems that have an evolutionary feature. Two real-life cases are illustrated to demonstrate the applicability of the methodology.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.4
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• pp.273-280
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• 2013

This paper presents novel OCS-LBP (Oriented Center Symmetric Local Binary Patterns) based on orientation of pixel gradient and image retrieval system based on BoF (Bag-of-Feature) and random forest classifier. Feature vectors extracted from training data are clustered into code book and each feature is transformed new BoF feature using code book. BoF features are applied to random forest for training and random forest having N classes is constructed by combining several decision trees. For testing, the same OCS-LBP feature is extracted from a query image and BoF is applied to trained random forest classifier. In contrast to conventional retrieval system, query image selects similar K-nearest neighbor (K-NN) classes after random forest is performed. Then, Top K similar images are retrieved from database images that are only labeled K-NN classes. Compared with other retrieval algorithms, the proposed method shows both fast processing time and improved retrieval performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.105-110
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• 2014

Feature-oriented software product line engineering is to develop various products by developing product line core assets in terms of features and composing those features. However, the developed product may not behave correctly if the feature interaction problem has not be properly taken into account during the feature composition. This paper proposes techniques for identifying and modularizing undesirable feature interactions effectively. The scientific calculator product line is used for evaluating the applicability of the proposed method.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.219-227
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• 2011

Service Oriented Architecture (SOA) is rapidly emerging as the efficient approach in contemporary complex, heterogeneous computing environments. SOA increases the adaptability by loose coupling and its main feature is that three elements such as service provider, service requester and service registry are connected with each other systematically. To design the service-oriented system efficiently, a metric to measure the coupling between services accurately is needed. In this paper, we propose four coupling metrics for SOA based softwares. First, we suggest a coupling metric for service-oriented systems by modifying an established coupling metric of object-oriented systems. Then we suggest another coupling metric which includes indirect coupling between services. We also suggest two relative coupling metrics to measure coupling between subsystems. We investigate the theoretical soundness of the proposed metrics by the axioms of Briand et al. Finally, we apply the presented metrics to an industrial-scale case study.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.317-318
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• 2016

국제수로기구(IHO)는 수로분야의 다양한 데이터와 서비스 표준개발을 위한 프레임워크인 S-100 표준을 개발 하였으며, 이를 기반으로 차세대 전자해도 표준을 포함하는 제품 및 서비스 표준을 개발하고 있다. S-100 기반 제품표준을 개발하기 위해서는 S-100 표준에 부합하는 Feature Catalogue(FC)가 포함되어야 하며, 이를 지원하기 위해 S-100 Feature Catalogue Builder(FCB)가 개발 되었다. S-100 FCB를 이용하여, FC제작 시 Feature를 정의하기 위해서는 Attribute를 매번 입력 하게 되는데, 공통 Attribute를 입력함에 있어서의 입력 오류와 장시간의 제작 시간이 소요된다는 문제점이 발생한다. 이러한 문제점은 현 S-100 FCB가 객체지향 개념이 고려되지 못한 것으로 판단하고, 본 연구에서는 OOP(Object-Oriented Programming) 기반의 S-100 FCB 개발 방안을 연구하였다. 이를 통해 중복되는 정보의 입력을 줄이고 제작 시간을 단축 할 수 있을 것으로 예상된다.