• Journal of the Korean Institute of Landscape Architecture
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• v.31 no.2
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• pp.58-69
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• 2003

The Hemi-sphere projection method produces an image that includes all surrounding visual landscape from a view point. This characteristic can solve the problem of perspective method that has only a limited view angle, and thus can be a potentially effective method for the analysis of visual landscape. This study tried to adopt the hemi-sphere projection method in the evaluation of streetscape, and examined its effectiveness and possibilities. Computer animations using the perspective method and the hemi-sphere method were produced for Bang-Hak Ro, Seoul, and the kames of the animations were reclassed to identify the visibility ratio of physical elements(buildings, sky and mountains). A preference questionnaire was given to 51 university students, and the relationships between the visibility ratio and visual preference were analyzed. The results showed that visual preference of streetscape can be explained by three factors: Openness, Uniformity, and Variousness, accounting for 63.2% of the total variance, and among which Openness showed the highest proportion at 32.1％. The visibility ratio calculated by the hemi-sphere method yielded strong correlation coefficients with Openness, and it was much higher than with the perspective method. The hemi-sphere method also produced significant correlation coefficients about Uniformity and Variousness, but the perspective method could not. The results demonstrated that the hemi-sphere method can provide more accurate observation of visual changes, and that it can be an effective method for the analysis of streetscape.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2341-2348
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• 1996

This paper proposes an image compression algorithm that adopts projection scheme on mean-residual metod. Sub-blocks of an image are encoded using mean-residual method where mean value is predicted according to that of neighboring blocks. Projection scheme with 8 directions is applied to the compression of residual signals of blocks. Projection vectors are finite-state vector quantized according to the projection angle of nighboring blocks in order to exploit the correlation among them. Side information to represent the repetition of projection is run-length coded while the information for projection direction is compressed using entropy encoding. The proposed scheme apears to be better in PSNR performance when compared with conventional projection scheme as well as in subjective quality preserving the edges of images better than most tranform methods which usually require heavy computation load.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.906-915
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• 2005

In this paper we propose content based image retrieval method using sequential clustering and projection information. Proposed method uses the mean of color in clustered color regions by sequential clustering and the projection information in each clustered color regions, which combines spatial information with color information in images efficiently. The experimental results showed that the proposed method retrieval efficiency improved 11.6 percent over conventional methods. In addition, the proposed method robustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.2
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• pp.29-36
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• 1999

It is shown that a new Krylov subspace method for solving symmetric indefinite systems of linear equations can be obtained. We call the method as the projection method in this paper. The residual vector of the projection method is maintained at each iteration, which may be useful in some applications.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.439-441
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• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.36-42
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• 2005

Purpose : To develop a novel approach to calculate the sensitivity profiles of the phased array coil for use in non-uniform intensity correction. Materials and Methods : The proposed intensity correction method estimates the sensitivity profile of the coil to extract intensity variations that represent the scanned image. The sensitivity profile is estimated by fitting a non-linear curve to various angles of projections through the imaged object in order to eliminate the high-frequency image content. Filtered back projection is then used to compute the estimates of the sensitivity profile of each coil. The method was applied both to phantom and brain images from 8-channel phased-array coil and 4-channel phased-array coil, respectively. Results : Intensity-corrected images from the proposed method have more uniform intensity than those from the commonly used 'sum-of-squares' approach. By using the proposed correction method, the intensity variation was reduced to $6.1\%$ from $13.1\%$, acquired from the 'sum-of-squares'. Conclusion : The proposed method is more effective at correcting the intensity non-uniformity of the phased-array surface-coil images than the conventional 'sum-of-squares' method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.327-335
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• 1998

Many kinds of map projection have been used, since this cannot be done without a distortion and seemless representation of the globe. To overcome the continues representation of large digital terrain information by the global coordinate system , to find out the sources of projection error and optimizing method, and to increase the map accuracy, specific map projection researches are needed. In this study, improvements of map projections are suggested for small scale mapping which covering entire Korean peninsula based on theoretical evaluation and limits of current map projection. Furthermore, distortion factors, positional errors, and accuracy increasing method are evaluated.

• Current Optics and Photonics
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• v.2 no.4
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• pp.332-339
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• 2018

A new multi-frequency fringe projection method is proposed to reduce the nonlinear phase error in 3-D shape measurements using an adaptive compensation method. The phase error of the traditional fringe projection technique originates from various sources such as lens distortion, the nonlinear imaging system and a nonsinusoidal fringe pattern that can be very difficult to model. Inherent possibility of phase error appearing hinders one from accurate 3-D reconstruction. In this work, an adaptive compensation algorithm is introduced to reduce adaptively the phase error resulting from the fringe projection profilometry. Three different frequencies are used for generating the gratings of projector and conveyed to the four-step phase-shifting procedure to measure the objects of very discontinuous surfaces. The 3-D shape results show that this proposed technique succeeds in reconstructing the 3-D shape of any type of objects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.911-914
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• 2011

Detecting Hand Region is essencial technology to providing User based interface and many research has been continue. In this paper will propose Hand Region Detection method by using HSV space based on Back Projection and Hand Shape Recognition using Hu Moment. By using Back Projection, I updated reliability on Hand Region Detection by Back Projection method and, Confirmed Hand Shape could be recognized through Hu moment.

• Structural Engineering and Mechanics
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• v.44 no.2
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• pp.179-196
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• 2012

An eigenspace projection clustering method is proposed for structural damage detection by combining projection algorithm and fuzzy clustering technique. The integrated procedure includes data selection, data normalization, projection, damage feature extraction, and clustering algorithm to structural damage assessment. The frequency response functions (FRFs) of the healthy and the damaged structure are used as initial data, median values of the projections are considered as damage features, and the fuzzy c-means (FCM) algorithm are used to categorize these features. The performance of the proposed method has been validated using a three-story frame structure built and tested by Los Alamos National Laboratory, USA. Two projection algorithms, namely principal component analysis (PCA) and kernel principal component analysis (KPCA), are compared for better extraction of damage features, further six kinds of distances adopted in FCM process are studied and discussed. The illustrated results reveal that the distance selection depends on the distribution of features. For the optimal choice of projections, it is recommended that the Cosine distance is used for the PCA while the Seuclidean distance and the Cityblock distance suitably used for the KPCA. The PCA method is recommended when a large amount of data need to be processed due to its higher correct decisions and less computational costs.