• Journal of International Society for Simulation Surgery
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• v.2 no.1
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• pp.7-9
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• 2015

Purpose In the many face-related application such as head pose estimation, 3D face modeling, facial appearance manipulation, the robust and fast facial feature extraction is necessary. We present the facial feature extraction method based on shape regression and feature selection for real-time facial feature extraction. Materials and Methods The facial features are initialized by statistical shape model and then the shape of facial features are deformed iteratively according to the texture pattern which is selected on the feature pool. Results We obtain fast and robust facial feature extraction result with error less than 4% and processing time less than 12 ms. The alignment error is measured by average of ratio of pixel difference to inter-ocular distance. Conclusion The accuracy and processing time of the method is enough to apply facial feature based application and can be used on the face beautification or 3D face modeling.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.995-1003
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• 2010

The content-based hashing for authentication and copy protection of image, video and 3D model has to satisfy the robustness and the security. For the security analysis of the hash value, the modelling method based on differential entropy had been presented. But this modelling can be only applied to the image hashing. This paper presents the modelling for the security analysis of the hash feature value in 3D model hashing based on differential entropy. The proposed security analysis modeling design the feature extracting methods of two types and then analyze the security of two feature values by using differential entropy modelling. In our experiment, we evaluated the security of feature extracting methods of two types and discussed about the trade-off relation of the security and the robustness of hash value.

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.135-144
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• 2007

Feature models are widely used in domain engineering phase of software product lines development to model the common and variable concepts among products. From the feature model, the feature configurations are generated by selecting the features to be included in target product. The feature configuration represents the requirements for the specific product to be implemented. Although there are a lot of researches on how to build and use the feature models and feature configurations, the researches on the formal semantics and reasoning of them are rather inactive. This paper proposes the feature configuration verification approach based on JESS, java-based rule-base system. The Graph Product Line, a standard problem for evaluating the software product line technologies, is used throughout the paper to illustrate this approach. The approach in this paper has advantage of presenting the exact reason causing inconsistency in the feature configuration. In addition, this approach should be easily applied into other software product lines development environments because JESS system can be easily integrated with Java language.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.10
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• pp.2446-2456
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• 1993

By virtue of progress of computer science, CAD/CAM technology has been developed greatly in each area. But the problems in the integration of CAD/CAM are not yet solved completely. The reason is that the exchange of data between CAD and CAM is difficult because the domains of design and manufacturing are different in nature. To solve this problem, a feature based modeller is developed in this study, which makes it possible to communicate between design and manufacturing through features. The modeller has feature, the concept of semi-bounded plane is introduced, and implemented as a B-rep sheet model using half-edge data structure. The features are then created on a part by local modification of the boundary on a part based on feature template information. This approach generalizes the modelling of features in a geometry model.

• MALSORI
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• no.67
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• pp.167-180
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• 2008

This paper describes a novel spectral envelope conversion method based on Gaussian mixture model (GMM). The core of this paper is rearranging source feature vectors in input space to the transformed feature vectors in feature space for the better modeling of GMM of source and target features. The quality of statistical modeling is dependent on the distribution and the dimension of data. The proposed method transforms both of the distribution and dimension of data and gives us the chance to model the same data with different configuration. Because the converted feature vectors should be on the input space, only source feature vectors are rearranged in the feature space and target feature vectors remain unchanged for the joint pdf of source and target features using KPCA. The experimental result shows that the proposed method outperforms the conventional GMM-based conversion method in various training environment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.30-36
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• 2004

The exchange of model design data among heterogeneous CAD systems is very difficult because each CAD system has different data structures suitable for its own functions. STEP represents product information in a common computer-interpretable form that is required to remain complete and consistent when the product information is needed to be exchanged among different computer systems. However, STEP has complex architecture to represent point, line, curve and vectors of element. Moreover it can't represent geometry data of feature based models. In this study, a structure of XML document that represents geometry data of feature based models as neutral format has been developed. To use the developed XML document, a converter also has been developed to exchange modules so that it can exchange feature based data models among heterogeneous CAD systems. Developed XML document and Converter have been applied to commercial CAD systems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.434-440
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• 2003

The exchange of model design date among heterogeneous CAD systems is a difficult task because each system has different data structures suitable for its own functions. STEP has been able to represent product information as a common computer-interpretable form that is required to remain complete and consistent when the product informant is needed to be exchanged among different computer system. However, STEP has difficult architecture in is representing point, line, curve and vectors of element, more over it can't represent geometry data of feature based models. In this study, a structure of XML document that represents geometry data of feature based models as neutral format has been developed. To use the developed XML document, a Converter has also been developed to exchange modules so that it can exchange feature based data models among heterogeneous CAD systems. Aa for evaluation of the developed XML document and Converter, Solidworks and SolidEdge are selected.

• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.432-443
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• 2005

Recent three-dimensional feature-based CAD systems based on solid or non-manifold modelling functionality have been widely used for product design in manufacturing companies. When product models associated with features are used in various downstream applications such as analysis, however, simplified and abstracted models at various levels of detail (LODs) are frequently more desirable and useful than the full detailed model. To provide multi-resolution models, the features need to be rearranged according to a criterion that measures the significance of the feature. However, if the features are rearranged, the resulting shape is possibly different from the original because union and subtraction Boolean operations are not commutative. To solve this problem, in this paper, the new concept of the effective zone of a feature is defined and identified using Boolean algebra. By introducing the effective zone, an arbitrary rearrangement of features becomes possible and arbitrary LOD criteria may be selected to suit various applications. Besides, because the effective zone of a feature is independent of the data structure of the model, the multi-resolution modelling algorithm based on the effective zone can be implemented on any 3D CAD system based on conventional solid representations as well as non-manifold topological (NMT) representations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.881-891
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• 2023

Recently, various studies on malicious URL detection using artificial intelligence have been conducted, and most of the research have shown great detection performance. However, not only does classical machine learning require a process of analyzing features, but the detection performance of a trained model also depends on the data analyst's ability. In this paper, we propose a DL-ML Fusion Hybrid Model for malicious web site URL detection based on URL lexical features. the propose model combines the automatic feature extraction layer of deep learning and classical machine learning to improve the feature engineering issue. 60,000 malicious and normal URLs were collected for the experiment and the results showed 23.98%p performance improvement in maximum. In addition, it was possible to train a model in an efficient way with the automation of feature engineering.

• Korean Journal of Computational Design and Engineering
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• v.10 no.4
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• pp.262-273
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• 2005

For CAD data users, few things are as frustrating as receiving CAD data that is unusable due to poor data quality. Users waste time trying to get better data, fixing the data, or even rebuilding the data from scratch from paper drawings or other sources. Most related works and commercial tools handle the boundary representation (B-Rep) shape of CAD models. However, we propose a design history?based approach for healing CAD model errors. Because the design history, which covers the features, the history tree, the parameterization data and constraints, reflects the design intent, CAD model errors can be healed by an interdependency analysis of the feature commands or of the parametric data of each feature command, and by the reconstruction of these feature commands through the rule-based reasoning of an expert system. Unlike other B Rep correction methods, our method automatically heals parametric feature models without translating them to a B-Rep shape, and it also preserves engineering information.