• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.548-553
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• 2010

This paper presents an effective shape image recognition method using the correlation based on 4-dimensional histogram. The histogram-based correlation is accurately applied to express the similarity by comparing the positions of a corresponding dimension between the images, which is calculated by considering 4 directions of the shape image. The correlation measure by using the normalized cross-correlation is also applied to obtain the robust recognition to the geometrical variations such as shape, position, size, and rotation. The proposed method has been applied to the problem for recognizing the 8 shape images of 64*64 pixels and the 30 shape images of 256*256 pixels. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.1-12
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• 2012

There are many trees in a roadside, parks or facilities for landscape. Although we are easily seeing a tree in around, it would be difficult to classify it and to get some information about it, such as its name, species and surroundings of the tree. To find them, you have to find the illustrated books for plants or search for them on internet. The important components of a tree are leaf, flower, bark, and so on. Generally we can classify the tree by its leaves. A leaf has the inherited features of the shape, vein, and so on. The shape is important role to decide what the tree is. And texture included in vein is also efficient feature to classify them. This paper evaluates the performance of a leaf classification system using both shape and texture features. We use Fourier descriptors for shape features, and both gray-level co-occurrence matrices and wavelets for texture features, and used combinations of such features for evaluation of images from the Flavia dataset. We compared the recognition rates and the precision-recall performances of these features. Various experiments showed that a combination of shape and texture gave better results for performance. The best came from the case of a combination of features of shape and texture with a flipped contour for a Fourier descriptor.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.585-588
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• 2008

This paper proposes hand gesture recognition using shape similarity method. For this, we require two steps which are aquisition of Hand area and similarity evaluation. First step is extracting hand area using YCbCr color spare. Then eliminate noise through filter and analyzing histogram. For doing this, we ran measure similarity of hand gesture by applying TSR after getting contour. Finally, we utilize shape similarity for recognizing of hand gesture.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.460-464
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• 1990

Texture provides an important source of information about the local orientation of visible surfaces. An important task that arises in many computer vision systems is the reconstruction of three-dimensional depth information from two-dimensional images. The surface orientation of texel is classified by the Artificial Neural Network. The classification method to recognize the shape of 3D object with artificial neural network requires less developing time comparing to conventional method. The segmentation problem is assumed to be solved. The surface in view is smooth and is covered with repeated texture elements. In this study, 3D shape reconstruct using interpolation method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.5
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• pp.45-51
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• 1997

To trnsmit moving image signals by using an object vased coding technique at the rate of 8kbps~11kbps, it is very important to minimize the bit rates used for the compression of the color information of MF-objects. This paper proposes a hybrid coding method which uses the shpae adaptive coding method and the interframe reference method selectively. Gilge's shape adaptive orthogonal coidng method is utilized for shpae adaptive coding. The interfarame reference method approximates the low-passed signals of the image by gilge's shpae adaptive orthogonalization method and then refers the approximation error signals from the high frequency signal components of th eprevious frame. The proposed method achives the bit rates reduction of 17% compared to the gilge's shape adaptive orthogonalization method and 30% rduction compared to the shape adaptive DCT in average.

• Tribology and Lubricants
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• v.15 no.3
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• pp.265-271
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• 1999

Wherever there are rotating equipment and contact between surface, there is wear and the generation of wear particles. The particles contained in the lubricating oil carry detailed and important information about the condition monitoring of the machine. This information may be deduced from particle shape, composition, size distribution, and concentration. Therefore, This paper was undertaken to Ferrography system of wear debris generated from lubricated moving machine surface. The lubricating wear test was performed under different experimental conditions using the Falex wear test of Pin and V-Block type by Ti(C, N) coated. It was shown from the test results that wear particle concentration (WPC) and wear severity Index( $I_{S}$), size distribution in normal and abnormal wear have come out all the higher value by increases sliding friction time. Wear shape is observed on the Ferrogram it was discovered a thin leaf wear debris as well as ball and plate type wear particles. This kind of large wear shape have an important effect not only metals damage, but also seizure phenomenon.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.3
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• pp.39-44
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• 2010

In this paper, we addressed a face transform scheme with age-progressing based on vector representation. Proposed approach utilized a vector modeling as well as morphing so as to improve not only a reliability but also a consistency. For the more, some elements of texture change owing to the face shape are defined and some parameters with respect to the internal and external environments are also considered. To testify the proposed approach, estimation of similarity is performed with qualitative manner by using experimental output, and finally resulted in satisfactory for face shape transformation aged from sixty to fourteen.

• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.251-254
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• 2010

게이트는 사람의 걸음걸이 특성을 나타내는 용어로, 게이트 인식의 경우 원 거리에서 획득한 정보만으로도 개개인을 인지할 수 있는 장점을 갖고 있다. 지문 인식이나 홍채 인식과 같은 기존의 생체 인식 방법은 사용자로 하여금 정보 제공을 위해 직접적인 접촉이나 근접 촬영 등 불편한 행위가 수반되어야 하는 반면, 게이트 인식은 이와 같은 단점이 없기 때문에 새로운 생체 인식 방법으로 많은 연구가 진행되고 있다. 그러나 게이트 인식의 경우 한 개인 간에도 내외부적인 요인에 의한 변화가 크기때문에 단순한 형태 특징만으로는 높은 인식 성능을 기대하기가 어렵다. 본 논문에서는 게이트 인식을 위해 단순한 형태 특징이 아닌 게이트 영상 시퀀스의 움직임에 대한 정보를 이용하기 위한 방안을 제안하고자 한다. 이를 위해 Shape Sequence를 도입하고 게이트 인식에 적용할 수 있는 방법을 제시한다.