• Journal of KIBIM
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• v.12 no.4
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• pp.19-31
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• 2022

With the development of 3D-based CAD (Computer Aided Design), attempts at freeform building design have expanded to small and medium-sized buildings in Korea. However, a standardized system for continuous utilization of shape data and BIM conversion process implemented with 3D-based NURBS is still immature. Without accurate review and management throughout the Freeform building project, interference between members occurs and the cost of the project increases. This is very detrimental to the project. To solve this problem, we proposed a continuous utilization process of 3D shape information based on BIM parameters. Our process includes algorithms such as Auto Split, Panel Optimization, Excel extraction based on shape information, BIM modeling through Adaptive Component, and BIM model utilization method using ID Code. The optimal cutting reference point was calculated and the optimal material specification was derived using the Panel Optimization algorithm. With the Adaptive Component design methodology, a BIM model conforming to the standard cross-section details and specifications was uniformly established. The automatic BIM conversion algorithm of shape data through Excel extraction created a BIM model without omission of data based on the optimized panel cutting reference point and cutting line. Finally, we analyzed how to use the BIM model built for automatic conversion. As a result of the analysis, in addition to the BIM utilization plan in the general construction stage such as visualization, interference review, quantity calculation, and construction simulation, an individual management plan for the unit panel was derived through ID data input. This study suggested an improvement process by linking the existing research on atypical panel optimization and the study of parameter-based BIM information management method. And it showed that it can solve the problems of existing Freeform building project.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.104-106
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• 2008

This paper proposes an image based method for arranging ship blocks in a dockyard. The problem of appropriately arranging numerous blocks has to be carefully planned because it has close relation to the effectiveness of the whole working process. To implement the system, the block shape and feature points have to be obtained from block image. The block arrangement system can be implemented by the fusion of the block shape extraction and image matching technology.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.57-64
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• 2006

Tn this paper, We propose a user friendly object-based multimedia retrieval system using the HCNN(HippoCampus Neural Network. Most existing approaches to content-based retrieval rely on query by example or user based low-level features such as color, shape, texture. In this paper we perform a scene change detection and key frame extraction for the compressed video stream that is video compression standard such as MPEG. We propose a method for automatic color object extraction and ACE(Adaptive Circular filter and Edge) of content-based multimedia retrieval system. And we compose multimedia retrieval system after learned by the HCNN such extracted features. Proposed HCNN makes an adaptive real-time content-based multimedia retrieval system using excitatory teaming method that forwards important features to long-term memories and inhibitory learning method that forwards unimportant features to short-term memories controlled by impression.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.583-594
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• 2000

The thinning process which is commonly used in extracting skeletons from handwritten Hangul characters has a problem of distorting the original pattern shapes. This paper proposes a method of skeleton extraction using a shape decomposition algorithm. We decompose the character pattern into a set of near convex parts using a shape decomposition algorithm. From the shape-decomposed pattern, we detect the joint parts and extract the skeletons from the parts incident to the joint parts. Then the skeletons not incident to the joint parts are extracted. Finally, the process of skeleton extension is performed to ensure the connectivity. We setup five criteria for the comparison of quality of skeletons extracted by our method and the thinning based method. The comparison shows the superiority of our method in terms of several criteria.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1827-1835
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• 2010

In this paper, facial feature areas in user picture are created by facial feature points extracted by ASM(Active Shape Model). In a existing virtual make-up application, users manually select a few features that are exactly. Users are uncomfortable with this method. We propose a virtual makeup application using ASM that does not require user input. In order to express a natural makeup, the modified alpha blendings for each cosmetic are used to blend skin color with cosmetic color. The Virtual makeup application was implemented to apply Foundation, Blush, Lip Stick, Lip Liner, Eye Pencil, Eye Liner and Eye Shadow.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.581-584
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• 1999

In order to retrieve the rotated image within database by the content based image retrieval system, the algorithms with rotation robustness is usually applied in the procedure of the feature extraction. In that case, it requires much calculation time for feature extraction and much indexed data for feature indexing. Thus. in this paper. we propose the rotation robust algorithm using the block variance of the projected vector. The algorithm does not require additional calculation for feature extraction and is executed within query time by comparing the extracted data. Proposed method can be processed through database including various size of images with shape information and executed with fast response time in implementation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.546-554
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• 2011

Near targets in the infrared (IR) images have the steady feature for inner region and the transient feature for the boundary region. Based on these features, this paper proposes a new method to extract the fine target shape of near targets in the IR images. First, we detect the boundary region of the candidate targets using the local variance weighted information entropy (WIE) of the original images. And then, a coarse target region can be estimated based on the labeling of the boundary region. For the coarse target region, we use the opening filter with an adaptive structure element to extract the fine target shape. The decision of the adaptive structure element size is optimized for the width information of target boundary by calculating the average WIE in the enlarged windows. The experimental results show that a proposed method has better extraction performance than the previous threshold algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.1076-1083
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• 2000

Vehicle license plate recognition identifies vehicle as a unique, and have many applications in traffic monitoring field. In this paper, a vertical edge based algorithm to extract license plate within input gray-scale image is proposed. A size-and-shape filter based on seed-filling algorithm is applied to remove the edges that are impossible to be the vertical edges of license plate. Then the remaining edges are matched with each other according to some restricted conditions so as to locate license plate in input image. After license plate is extracted. normalized and segmented, the characters on it are recognized by template matching method. Experimental results show that the proposed algorithm can deal with license plates in normal shape effectively, as well as the license plates that are out of shape due to the angle of view.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.869-872
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• 2000

Although many content-based image retrieval systems using shape feature have tried to cover rotation-, position- and scale-invariance between images, there have been problems to cover three kinds of variance at the same time. In this paper, we introduce new approach to extract shape feature from image using MBR(Minimum Bounding Rectangle). The proposed method scans image for extracting MBR information and, based on MBR information, compute contour information that consists of 16 points. The extracted information is converted to specific values by normalization and rotation. The proposed method can cover three kinds of invariance at the same time. We implemented our method and carried out experiments. We constructed R*_tree indexing structure, perform k-nearest neighbor search from query image, and demonstrate the capability and usefulness of our method.

• Journal of Digital Policy
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• v.1 no.2
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• pp.53-59
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• 2022

In this paper, we proposed a method using sub-edge information extracted through a hierarchical structure in the process of generating super resolution based on a single image. In order to improve the quality of super resolution, it is necessary to clearly distinguish the shape of each area while clearly expressing the boundary area in the image. The proposed method assists edge information of the image in deep learning based super resolution method to create an improved super resolution result while maintaining the structural shape of the boundary region, which is an important factor determining the quality in the super resolution process. In addition to the group convolution structure for performing deep learning based super resolution, a separate hierarchical edge accumulation extraction process based on high-frequency band information for sub-edge extraction is proposed, and a method of using it as an auxiliary feature is proposed. Experimental results showed about 1% performance improvement in PSNR and SSIM compared to the existing super resolution.