• Journal of the Korean Society of Costume
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• v.56 no.9 s.109
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• pp.14-23
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• 2006

The purpose of this study is to identify the esthetic features of femme fatale character fashions, which are shown in Movie . The feature of evil femineity is the attribute of evil which brings men to ruin by the dangerous, cunning, and cruel trick, and is expressed in black color, red color, and slash fashion. This fashion shows the dark reverse side of women's sexual desire in relation to anxiety, evil, and death. The feature of sensuality evokes physical pleasures or desires, and maximizes the exposure of sexual regions by tightening or loosening women's body. In the fashion expressing this feature, the forms are fit or loose silhouette. and the colors are black and red. and the materials are soft. This fashion seems to deconstruct the past concept of sex consciousness and emphasize the independent and autonomous femineity. The feature of positiveness combines feminine elements with masculine elements in relation to power elements. This feature is expressed in tailored suit and trousers, with few patterns and details, and in black color and gray color. This fashion reflects the aggressive, challenging, and independent femineity, and expresses the potential defense for the weakness and danger of female body. The feature of purity expresses the earnest and truthful mind, and is expressed in the soft and light one-piece dress, the elegant suit, and the pink color and black color fashion. This fashion shows angel-like and reliable womanly beauty, but at the same time shows women's attribute which changes their behavior and thinking every moment, so that this fashion shows women's double-sided attribute which combines women's weakness and violence, or tenacity and conflict.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.951-954
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• 1998

This paper describes the implementation of the machine vision system and the method of classifying the objects. Its system described in this paper is consisted of robot, conveyer system, warehouse, and machine vision. This system first recognizes the object on conveyer, and then robot moves it to the warehouse. The position of the object on conveyer is always not constant, because it is not easy to extract the feature of its object and classify it into one of several categories. In this paper, to classify or inspect the pattern of the object, we propose the method of template matching using feature vector such as position invariant moment and mophological operation such as opening and closing. And we indentified an unregistered object using unsuperviser learning method and assigned it to the new pattern. We implemented its system and obtained satisfied results.

• Journal of the Korean Society of Costume
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• v.38
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• pp.31-49
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• 1998

This study is the primary basic study about the spatial feature of modeling of Fashion Design. Then, this researcher lays significance in establishing the basic system about the character of dress and its ornaments as modeling in spatial-formal, dimension, examining the feature of modeling closely through perception principle and offering the basic principle to plan and organize the modeling space for dress and its ornaments on the basis of it. To generalize the findings is as follows : First, the spatial system of modeling for dress and its ornaments is made with 3 elements such as space, human beings and dress and its ornaments. Second, the form of dress and its ornaments and the spatial organization start from the structural basis which is human body, and the sensible system of body is made through inter-action, but the aesthetic expression is complet-ed by the moment of body. Third, the characteristic principle of model-ing for dress and its ornaments which was suggested in Chapter IV is based on the visuo-per-ceptional modeling experience, and these thinking contents are inputted in cognition course as the invisible in formation in the new space plan and organization and activate the apperception course and aim at the action about aesthetic judgement.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.156-161
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• 1997

Zernike moments have been one of the most commonly used feature vectors for recognizing rotated patterns due to its rotation invariant characteristics. In order to reduce its expensive computational cost, several methods have been proposed to lower the complexity. One of the methods proposed by mukundan and K. R. Ramakrishnan[1], however, is not rotation invariant. In this paper, we propose another method that not only reduces the computational cost but preserves the rotation invariant characteristics. In the experiment, we compare our method with others, in terms of computing time and the accuracy of moment feature at different rotational angle of an object in image.

• Journal of the Korean Geophysical Society
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• v.9 no.3
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• pp.249-262
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• 2006

The 29 May 2004 offshore Uljin, Korea earthquake was predominantly thrust-faulting at a depth of approximately 12 (±2) km. The mainshock attained the seismic moment of M0 =5.41 (±1.87)  1016 N m (Mw = 5.1). The focal mechanism indicates a subhorizontal P-axis trending 264° and plunging 2°. The orientation of P- and T-axis is consistent with the direction of absolute plate motion generally observed within the plates, hence the cause of the May 29 shock is the broad-scale stress pattern from the forces acting on the downgoing slab along the Japan trench and inhibiting forces balancing it. The 29 May 2004 earthquake occurred along a deep seated (~12 km), pre-existing feature that is expressed on the surface as the basement escarpment along the western and southern slopes of the Ulleung basin. The concentrated seismicity along this basement escarpment suggests that this feature may qualify as a seismic zone - the Ulleung basement escarpment seismic zone (UBESZ).

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1484-1486
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• 2001

In this study, The underwater object recognition using ultrasonic sensor fabricated with porous PZT-Polymer 3-3 type composites and invariant moment vector and SOFM(Self Organizing Feature Map) neural networks are presented. The recognition rates for the training data and the testing data were 98% and 94%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.585-589
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• 2002

In this paper, hierarchical retrieval system based on efficient feature extraction is proposed. In order to retrieval the image with robustness for geometrical transformation such as translation, scaling, and rotation. After performing the 2-level wavelet transform on image, We extract moment in low-level subband which was subdivided into subimages and texture feature, contrast of GLCM(Gray Level Co-occurrence Matrix). At first we retrieve the candidate images in database by the ones of image. To perform a more accurate image retrieval, the edge information on the high-level subband was subdivided horizontally, vertically and diagonally. And then, the energy rate of edge per direction was determined and used to compare the energy rate of edge between images for higher accuracy.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.415-425
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• 2002

In this paper, we present a content-based image retrieval method which is based on the feature extraction in the wavelet transform domain. In order to overcome the drawbacks of the feature vector making up methods which use the global wavelet coefficients in subbands, we utilize the energy value of wavelet coefficients, and the shape-based retrieval of objects is processed by moment which is invariant in translation, scaling, rotation of the objects The proposed methods reduce feature vector size, and make progress performance of classification retrieval which provides fast retrievals times. To offer the abilities of region-based image retrieval, we discussed the image segmentation method which can reduce the effect of an irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The region-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.434-441
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• 2001

We present an image retrieval method for improving retrieval performance by the effective fusion of spatial histogram and wavelet moments. In this method, the similarity for spatial histograms and the similarity for wavelet moment are effectively fused in the computation of the similarity between a query image and DB image. That is, the wavelet moments feature represented in multi-resolution and the spatial histogram feature robust to translation and rotation are used to improve retrieval performance. In order to evaluate the performance of the proposed method, we use Brodatz texture DB, MPEG-7 T1 DB, and Corel Draw Photo DB. Experimental results show that the proposed method yields 5.3% and 13.8% better Performances for Brodatz DB, and 15.5% and 3.2% better Performances for Corel Draw Photo DB over the histogram method and the wavelet moment method, respectively.