• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.1-11
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• 2012

Computed tomography (CT) images are widely used for the analysis of the temporal evaluation or monitoring of the progression of a disease. The follow-up examinations of CT scan images of the same patient require a 3D registration technique. In this paper, an automatic and robust registration is proposed for the rigid registration of 3D CT images. The proposed method involves two steps. Firstly, the two CT volumes are aligned based on their principal axes, and then, the alignment from the previous step is refined by the optimization of the similarity score of the image's voxel. Normalized cross correlation (NCC) is used as a similarity metric and a downhill simplex method is employed to find out the optimal score. The performance of the algorithm is evaluated on phantom images and knee synthetic CT images. By the extraction of the initial transformation parameters with principal axis of the binary volumes, the searching space to find out the parameters is reduced in the optimization step. Thus, the overall registration time is algorithmically decreased without the deterioration of the accuracy. The preliminary experimental results of the study demonstrate that the proposed method can be applied to rigid registration problems of real patient images.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.7
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• pp.340-353
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• 2008

A computational color palette extraction model is introduced to describe paint brush objectively and efficiently. In this model, a color palette is defined as a minimum set of colors in which a painting can be displayed within error allowance and extracted by the two step processing of color grouping and major color extraction. The color grouping controls the resolution of colors adaptively and produces a basic color set of given painting images. The final palette is obtained from the basic color set by applying weighted k-means clustering algorithm. The extracted palettes from several famous painters are displayed in a 3-D color space to show the distinctive palette styles using RGB and CIE LAB color models individually. And the two experiments of painter classification and color transform of photographic image has been done to check the performance of the proposed method. The results shows the possibility that the proposed palette model can be a computational color analysis metric to describe the paint brush, and can be a color transform tool for computer graphics.

• Journal of KIISE
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• v.43 no.9
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• pp.1034-1042
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• 2016

Together with machine-learning frameworks, area-based imagery registration techniques can be easily applied to diverse types of image pairs without predefined features and feature descriptors. However, feature detectors are often used to quickly identify candidate image patch pairs, limiting the applicability of these registration techniques. In this paper, we propose a ConvNet (Convolutional Network) "Dart" that provides not only the matching metric between patches, but also information about their distance, which are helpful in reducing the search space of the corresponding patch pairs. In addition, we propose a ConvNet "Fad" to identify the patches that are difficult for Dart to improve the accuracy of registration. These two networks were successfully implemented using Deep Learning with the help of a number of training instances generated from a few registered image pairs, and were successfully applied to solve a simple image registration problem, suggesting that this line of research is promising.

• International Journal of High-Rise Buildings
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• v.6 no.2
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• pp.165-175
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• 2017

The importance of designing urban building complexes so that they obtain 'urban' power, rather than become isolated from the surrounding urban context, has been well recognized by both researchers and practitioners. Nevertheless, most current discussions are made from architects' personal experiences and intuition, and lack a quantitative understanding, to which obstacles include an in-depth exploration of the 'urban' power between building complexes and the urban environment. This paper attempts to measure this feature of 'urban', i.e., 'urbanity,' through a new analytical approach derived from the opendata environment. Three measurements that can be easily collected though the Google Maps API and Open Street Map are applied herein to evaluate high or low values of urbanity. Specifically, these are 'metric depth', i.e., the scale of extended public space, 'development density', i.e., density and distribution of point of interests (POIs), and 'type diversity', i.e., diversity of different commercial types. Six cases located in Japan, China and Hong Kong respectively are ranked based on this analytical approach and compared with each other. It shows that Japanese cases, i.e., Osaka Station City and Namba Parks, Osaka, obtained clearly higher values than cases in Shanghai and Hong Kong. On one hand, the insight generated from measuring and explaining 'urban' power would help to assist better implementation of this feature in the design of urban building complexes. On the other hand, this analytical approach can be easily extended to achieve a large-scale measurement and comparison among different urban building complexes, which is also helpful for design practitioners.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.101-115
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• 2008

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.1-8
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• 2010

The key challenge in HW/SW co-design is how to choose the appropriate HW/SW partitioning from the vast array of possible options in the mapping set. In this paper we present a unique and efficient approach for addressing this problem known as Customized Heuristic Algorithm for Reducing Mapping Sets(CHARMS). CHARMS uses sensitivity to individual task computational complexity as well the computed weighted values of system performance influencing metrics to streamline the mapping sets and extract the most optimal cases. Using H.263 encoder, we show that CHARMS sieves out 95.17% of the sub-optimal mapping sets, leaving the designer with 4.83% of the best cases to select from for run-time implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.435-449
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• 2023

The state-of-the-art video-based point cloud compression(V-PCC) has a high efficiency of compressing 3D point cloud by projecting points onto 2D images. These images are then padded and compressed by High-Efficiency Video Coding(HEVC). Pixels in padded 2D images are classified into three groups including origin pixels, padded pixels and unoccupied pixels. Origin pixels are generated from projection of 3D point cloud. Padded pixels and unoccupied pixels are generated by copying values from origin pixels during image padding. For padded pixels, they are reconstructed to 3D space during geometry reconstruction as well as origin pixels. For unoccupied pixels, they are not reconstructed. The rate distortion optimization(RDO) used in HEVC is mainly aimed at keeping the balance between video distortion and video bitrates. However, traditional RDO is unreliable for padded pixels and unoccupied pixels, which leads to significant waste of bits in geometry reconstruction. In this paper, we propose a new RDO scheme which takes 3D-Distortion into account instead of traditional video distortion for padded pixels and unoccupied pixels. Firstly, these pixels are classified based on the occupancy map. Secondly, different strategies are applied to these pixels to calculate their 3D-Distortions. Finally, the obtained 3D-Distortions replace the sum square error(SSE) during the full RDO process in intra prediction and inter prediction. The proposed method is applied to geometry frames. Experimental results show that the proposed algorithm achieves an average of 31.41% and 6.14% bitrate saving for D1 metric in Random Access setting and All Intra setting on geometry videos compared with V-PCC anchor.

• Journal of the Korean Society of Costume
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• v.30
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• pp.69-84
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• 1996

The main current of ancient Korean thought is based on Yuk(易) : which solves the principle of creation of universe letter(文字) which is the principle of geometry and three elements thought of circle square . It's related to the creation principle of the universe and regarded as a sign that demons-trates shows the way to read the mathematical principle. The original form of Korean clothes(Han-Bock, 韓服) is represents the structure of hu-man body which reflects a small universe. So a good structure and meaning of the human body is well read in the formation of Korean clothes(Han-Bock, 韓服) and that is a good symbolization of the clothes(Han-Bock, 韓服) as the space of small universe. The good formation of Korean clothes(Han-Bock, 韓服) could be shown by cutting out straight bending twisting and turning each straitly cutting piece is applied to its trans-tormation. Geametical formation with obvious sym-metric dividing of front-back left-right and top-bottom is well shown in Korean clothes by twisting Yuk(易) or m bius strips. So we can find out whole formation by representing only either 'front and back' or 'left and right' and also sa-pok(사폭) of man's trousers seop(섶) of jeo-go-ri(short jacket 저고리) kyut-ma-gi(곁마기) of Sam-hwai-jang jeo-go-ri (삼회장 저고리), mu(무) of jig-ryung(straight collar and long and wide sleeved robe, 直領) trouser wide and ga-rae-ba-dae(가래바대) of dan-cok-kok(woman's under trousers). The formation line of Korean clothes(Han-Bock, 韓服) is based on theprinciple of unlimited m bius strips by twisting of turning direction from universal principle and original basic form is not changd even by turning in-side out. Unity of the whole and part in Korean clothes(Han-Bock, 韓服) could be found in nonorientable thought(非始原思想) which represents the unity and dependence kil(길) of jeo-go-ri(short jacket, 저고리) and po(long and wide sleeved robe, 袍). Selva-gewise(식서방향) of sleeves and seam of out-side of kil(길) and outside of seop(섶) are directed to outside of seop(섶) inside of seop(섶) is to kil and direction of inseam of kheut-dong(끝동) and kyut-ma-gi(곁마기) is directed to sleeves. Korean clothes(Han-Bock, 韓服) is usually made by cutting fabric for several parts and sewing them and the way to make Korean clothes is deeply related to the theory of chon-pu-kyung jong-il and il-seok -sam-geuk. As the development of men's consciousness is pro-gressed from total separation to separation and superseparation. Sewing process of korean clothes(Han-Bock, 韓服) can be make single dimension to double or triple dimension of korean clothes(Han-Bock, 韓服) silhoutte bacause it can be include principle of topology as noneuclity.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.9-20
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• 2005

Recently, the MPEG-7 standard a multimedia content description standard is wide]y used for content based image/video retrieval systems. However, since the descriptors standardized in MPEG-7 are usually multidimensional and the problem called 'Curse of dimensionality', previously proposed indexing methods(for example, multidimensional indexing methods, dimensionality reduction methods, filtering methods, and so on) could not be used to effectively index the multimedia database represented in MPEG-7. This paper proposes an efficient multimedia data indexing mechanism reflecting the characteristics of MPEG-7 visual descriptors. In the proposed indexing mechanism, the descriptor is transformed into a histogram of some attributes. By representing the value of each bin as a binary number, the histogram itself that is a visual descriptor for the object in multimedia database could be represented as a bit string. Bit strings for all objects in multimedia database are collected to form an index file, bitmap index, in the proposed indexing mechanism. By XORing them with the descriptors for query object, the candidate solutions for similarity search could be computed easily and they are checked again with query object to precisely compute the similarity with exact metric such as Ll-norm. These indexing and searching mechanisms are efficient because the filtering process is performed by simple bit-operation and it reduces the search space dramatically. Upon experimental results with more than 100,000 real images, the proposed indexing and searching mechanisms are about IS times faster than the sequential searching with more than 90% accuracy.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.371-376
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• 2006

The initial radius of sphere decoder has great effect on the bit error rate performance and computational complexity. Until now, it has been determined either by considering the statistical property of channel or by using of MMSE solution. The initial radius obtained by using statistical property of channel includes the lattice point corresponding to the transmit signal vector with very high probability. The method using MMSE solution first calculates out the MMSE solution of the received signal, then maps the hard decision of this solution into the received signal space, and finally the distance between the mapped point and the received signal is selected as the initial radius of the sphere decoding. In this paper, we derive a simple equation for initial radius selection which uses statistical property of channel and compare it with the method using MMSE solution. To compare two methods we define new metric 'Tightness'. Through the simulation, we observe that in low and moderate SNR region, the method using MMSE solution provides more complexity reduction for decoding while in high SNR region, the method using channel statistics is better.