• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.207-211
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• 2011

This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7C
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• pp.428-434
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• 2011

Recently, subspace analysis has raised its performance to a higher level through the adoption of kernel-based nonlinearity. Especially, the radial basis function, based on its nonparametric nature, has shown promising results in face recognition. However, due to the endemic small sample size problem of face data, the conventional kernel-based feature extraction methods have difficulty in data representation. In this paper, we introduce a novel variant of the RBF kernel to alleviate this problem. By adopting the concept of the nearest feature line classifier, we show both effectiveness and generalizability of the proposed method, particularly regarding the small sample size issue.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.702-706
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• 1995

Integration of CAM and CAM information is important in the CIM era. For a CIM system, the feature representation can be a solution to the integration of product model data. These are geometry feature, functional feature, and manufacturing feature in the feature context. This paper proposes a framework to integrate the configuration design method, parametric modeling and the feature modeling method. The concept of design unit which is one level higher than functional feature and parametric modeling concept with functional features have been proposed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.322-326
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• 2004

This paper describes a new iris recognition method based on a shift-invariant wavelet sub-images. For the feature representation, we first preprocess an iris image for the compensation of the variation of the iris and for the easy implementation of the wavelet transform. Then, we decompose the preprocessed iris image into multiple subband images using a shift-invariant wavelet transform. For feature representation, we select a set of subband images, which have rich information for the classification of various iris patterns and robust to noises. In order to reduce the size of the feature vector, we quantize. each pixel of subband images using the Lloyd-Max quantization method Each feature element is represented by one of quantization levels, and a set of these feature element is the feature vector. When the quantization is very coarse, the quantized level does not have much information about the image pixel value. Therefore, we define a new similarity measure based on mutual information between two features. With this similarity measure, the size of the feature vector can be reduced without much degradation of performance. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.701-710
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• 2014

The analysis on the characteristics of the signification system of Japanese feature-length animations that this essay centrally deals with eventually examines the characteristics of representation and communication in Japanese feature-length animations. In general, most animation works focusing on characters and stories contain the signification systems related to 'denotation' and connotation.' However, tendency of the aesthetic representation and communication that appears differently, depending on the characteristics of the signification system that each animation work pursues. From this point of view, Japanese feature-length animation emphasizes connotative signification system and aesthetic representation, unlike Disney animation that strongly shows the tendency that makes the audience directly immersed in the theme and message of the work conveyed further in the myths by pursuing denotative signification system. And, in the case of Japanese feature-length animation, the 'dissenting and arbitrary interpretation' of the theme, the message that the animation work intends to convey and myths pursued is bound to appear diversely, depending on the audience's experiences and cultural and social backgrounds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.131-146
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• 2021

Multimodal biometric-based recognition has been an active topic because of its higher convenience in recent years. Due to high user convenience of finger, finger-based personal identification has been widely used in practice. Hence, taking Finger-Print (FP), Finger-Vein (FV) and Finger-Knuckle-Print (FKP) as the ingredients of characteristic, their feature representation were helpful for improving the universality and reliability in identification. To usefully fuse the multimodal finger-features together, a new robust representation algorithm was proposed based on hierarchical model. Firstly, to obtain more robust features, the feature maps were obtained by Gabor magnitude feature coding and then described by Local Binary Pattern (LBP). Secondly, the LGBP-based feature maps were processed hierarchically in bottom-up mode by variable rectangle and circle granules, respectively. Finally, the intension of each granule was represented by Local-invariant Gray Features (LGFs) and called Hierarchical Local-Gabor-based Gray Invariant Features (HLGGIFs). Experiment results revealed that the proposed algorithm is capable of improving rotation variation of finger-pose, and achieving lower Equal Error Rate (EER) in our homemade database.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.10
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• pp.1305-1313
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• 2013

In this study, a method to apply feature-based simplification to boundary representation models is proposed. For feature-based simplification, a volume decomposition tree is created from a boundary representation model. The volume decomposition tree is represented by regularized Boolean operations of additive volumes, subtractive volumes, and fillet/round/chamfer volumes, and it is generated by stepwise volume decomposition, which consists of fillet/round/chamfer decomposition, wrap-around decomposition, volume split decomposition, and cell-based decomposition. After the volume decomposition tree is transformed to an infix expression, the CAD model can be simplified by reordering the volumes. To verify the proposed method, a prototype system was implemented, and experiments on test cases were conducted. From the results of the experiments, it is verified that the proposed method is useful for simplifying CAD models based on boundary representation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.147-153
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• 2017

Efficient texture representation is very important in computer vision fields. The performance of texture classification or/and segmentation can be improved based on efficient texture representation. Gabor filter is a representation method that has long history for texture representation based on multi-scale analysis. Gabor filter shows good performance in texture classification and segmentation but requires much processing time. In this paper, we propose new texture representation method that is also based on multi-scale analysis. The proposed representation can provide similar performance in texture classification but can reduce processing time against Gabor filter. Experimental results show good performance of our method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.833-835
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• 2002

In this paper, we propose multi-resolutional representation of B-rep solid models using the selective Boolean operations on non-manifold geometric models. Since the union and subtraction operations of the selective Boolean operations are commutative, the integrity of the model is guaranteed for reordering design features. A multi-resolution representation is established using a non-manifold merged set model and a feature modeling tree reordered according to some criterion of level of detail (LOD). Then, a solid model for a specified LOD can be extracted from this multi-resolution model using the selective Boolean operations.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.61-64
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• 2002

In this paper, we propose the iris feature extraction by using statistical methods. There are many approaches for iris feature extraction, but most of them require a set of parameters that one should choose for the transformation to obtain a useful representation of the iris. It would be most useful to estimate the method of the iris feature extraction from iris itself. Therefore, we apply the unsupervised statistical methods for the iris feature extraction.