• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1001-1014
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• 2003

In a feature modeling, problems such as ambiguities, interpretation errors, incompleteness, etc caused by informal specification occur in the modeling phase. Therefore, feature specification method and processes are suggested in this paper to resolve these problems. The structure and language of feature modeling is defined in this paper to specify various features. First, this feature model is abstracted in the meta-level to get predicates and attributes. Formal feature model specification method is proposed using multi-paradigm language. Second, Feature specification process is proposed to describe how to specify feature formally. And third, Feature interaction management is defined to solve the problems caused between specified features. Finally, the proposed feature specification method is applied to Distributed Meeting Scheduler System domain.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.287-290
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• 2000

In this paper we have presented approach to automatic the direction feature vectors detection, which detects the ridge line directly in gray scale images. In spite of a greater conceptual complexity, we have shown that our technique has less computational complexity than the complexity of the techniques which require binarization and thinning. Afterwards a various direction feature vectors is changed four direction feature vectors. In this paper used matching method is four direction feature vectors based matching. This four direction feature vectors consist feature patterns in fingerprint images. This feature patterns were used for identification of individuals inputed multilayer Neural Networks(NN) which has capability of excellent pattern identification.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.835-838
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• 2008

In this paper, we present automatic face detection and tracking which is robustness in rotation and translation. Detecting a face image, we used Haar-like feature, which is fast detect facial image. Also tracking, we applied Lucas-Kanade feature tracker and KLT algorithm, which has robustness for rotated facial image. In experiment result, we confirmed that face detection and tracking which is robustness in rotation and translation.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.6
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• pp.176-184
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• 2000

Reverse engineering (RE) is a process to create computer aided design (CAD) models from the scanned data of an existing part acquired using 3D position scanners. This paper proposes a novel methodology of extracting geometric features directly from a set of 3D scanned points, which utilizes the concepts of feature-based technology and artificial neural networks (ANNs). The use of ANN has enabled the development of a flexible feature-based RE application that can be trained to deal with various features. The following four main tasks were mainly investigated and implemented: (1) Data reduction; (2) edge detection; (3) ANN-based feature recognition; (4) feature extraction. This approach was validated with a variety of real industrial components. The test results show that the developed feature-based RE application proved to be suitable for reconstructing prismatic features such as block, pocket, step, slot, hole, and boss, which are very common and crucial in mechanical engineering products.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.267-271
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• 1993

Developed in this paper is a feature based modeling of welded plate construction(WPC) which is composed of flat or bended plates represented as reference plane with a constant thickness. First, the necessity and the characteristics of the feature based modeling of WPC as compared with the assemblies of mechanical parts are investigated. Second, feature library for the assemblied of WPC is shown which contains several types of features like joint feature, groove feature, materialfeature and precision feature. Third, the assembly procedures are presented whichmainly consist of both the assembly transformation and the correct assembly checking. Fourth, weld lines generated in the assembled WPC are defined so that those can be used in the process planning or the manufacturing stage. Finally, A prototype system isdeveloped by using a geometric modeling software Pro/Engineer, a graphic software GL(Graphic Library), and C language on a CAD workstation IRIS.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.35-42
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• 2008

This study introduces a robust feature detector for sonar data from a general fixed-type of sonar ring. The detector is composed of a data association filter and a feature extractor. The data association filter removes false returns provided frequently from sonar sensors, and classifies set of data from various objects and robot positions into a group in which all the data are from the same object. The feature extractor calculates the geometries of the feature for the group. We show the possibility of extracting circle feature as well as a line and a point features. The proposed method was applied to a real home environment with a real robot.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.130-141
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• 2017

Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.

• Speech Sciences
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• v.6
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• pp.103-117
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• 1999

This paper suggests that the onset-coda asymmetry found in languages like Korean and others should be dealt with in terms of one acoustic feature rather than other articulatory features, claiming that the acoustic feature involved here is [noise], i.e., 'aperiodic waveform energy'. It determines the structural well-formedness of the languages in question whether a coda ends in [noise] or not, regardless of the intensity, the frequency, and the time duration of the [noise]. Fricatives, affricates, aspirated stops, tense stops, and released stops are all disallowed in the coda position due to the acoustic feature [noise] they, commonly end with if they were, posited in the coda. The proposal implies that the three seemingly separate prohibitions of consonants in the coda position -- i) no fricatives/affricates, ii) no aspirated/tense stops, and iii) no released stops -- are directly correlated with each other. Incorporation of the one acoustic feature [noise] in the feature theory enables us to see that the aspects of onset-coda asymmetry are derived from one single source: ban, of [noise] in the coda.

• ETRI Journal
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• v.38 no.3
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• pp.502-509
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• 2016

Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, and $135^{\circ}$) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation.

• 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.