• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.63-70
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• 2009

3D GIS(Geographic Information System) processes, analyzes and presents various real-world 3D phenomena by building 3D spatial information of real-world terrain, facilities, etc., and working with visualization technique such as VR(Virtual Reality). It can be applied to such areas as urban management system, traffic information system, environment management system, disaster management system, ocean management system, etc,. In this paper, we propose video visualization technology based on 3D geographic information to provide effectively real-time information in 3D geographic information system and also present methods for establishing 3D building information data. The proposed video visualization system can provide real-time video information based on 3D geographic information by projecting real-time video stream from network video camera onto 3D geographic objects and applying texture-mapping of video frames onto terrain, facilities, etc.. In this paper, we developed sem i-automatic DBM(Digital Building Model) building technique using both aerial im age and LiDAR data for 3D Projective Texture Mapping. 3D geographic information system currently provide static visualization information and the proposed method can replace previous static visualization information with real video information. The proposed method can be used in location-based decision-making system by providing real-time visualization information, and moreover, it can be used to provide intelligent context-aware service based on geographic information.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.147-161
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• 2021

Through photogrammetry techniques, what current researches can achieve at present is rough 3D mesh and color map of objects, rather than usable photo-realistic 3D assets. This research aims to propose a new method to create photo-realistic 3D assets that can be used in the field of visualization applications. The new method combines photogrammetry with computer graphics modeling. Through the description of the production process of three objects in the real world - "Bullet Box", "Gun" and "Metal Beverage Bottle," it introduces in details the concept, functions, operating skills and software packages used in the steps including the photograph object, white balance, reconstruction, cleanup reconstruction, retopology, UV unwrapping, projection, texture baking, De-Lighting and Create Material Maps. In order to increase the flexibility of the method, alternatives to the software packages are also recommended for each step. In this research, 3D assets are produced that are accurate in shape, correct in color, easy to render and can be physically interacted with dynamic lighting in texture. The new method can obtain more realistic visual effects at a faster speed. It does not require large-scale teams, expensive equipment and software packages, therefore it is suitable for small studios and independent artists and educational institutions.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.151-157
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• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.307-312
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• 2017

The purpose of this paper is to develop a new type of RGB lighting pipeline that can save time in animation production. After identifying the problems of the current method, the researchers studied 8 steps through new methods and comparative analysis. A method of implementing a graphic image lighting effect by the RGB lighting pipeline according to the current method is to create a render layer for each light set and a set of digital light separated by texture, Three types of written information can be stored in one layer and graphic image, and the accuracy and precision of color correction can be improved. Through this study, we propose the new and improved RGB lighting pipeline according to the characteristics of the work and the industries.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1027-1036
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• 2020

In this study, a cloud-based processing method using Agisoft Metashape, a commercial software, and Amazon web service, a cloud computing service, is introduced and evaluated to quickly generate high-precision 3D realistic data from large volume UAV images acquired in disaster sites. Compared with on-premises method using a local computer and cloud services provided by Agisoft and Pix4D, the processes of aerial triangulation, 3D point cloud and DSM generation, mesh and texture generation, ortho-mosaic image production recorded similar time duration. The cloud method required uploading and downloading time for large volume data, but it showed a clear advantage that in situ processing was practically possible. In both the on-premises and cloud methods, there is a difference in processing time depending on the performance of the CPU and GPU, but notso much asin a performance benchmark. However, it wasfound that a laptop computer equipped with a low-performance GPU takes too much time to apply to in situ processing.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.777-785
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• 2017

In the modern real world, we can extract and recognize some texts to get a lot of information from the scene containing them, so the techniques for extracting and recognizing text areas from a scene are constantly evolving. They can be largely divided into texture-based method, connected component method, and mixture of both. Texture-based method finds and extracts text based on the fact that text and others have different values such as image color and brightness. Connected component method is determined by using the geometrical properties after making similar pixels adjacent to each pixel to the connection element. In this paper, we propose a method to adaptively change to improve the accuracy of text region extraction, detect and correct the slope of the image using edge and image segmentation. The method only extracts the exact area containing the text by correcting the slope of the image, so that the extracting rate is 15% more accurate than MSER and 10% more accurate than EEMSER.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.503-508
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• 2003

Since surgical treatment of the spine should overcome neurological compromises, the operative procedures need to be carefully planned and carried out with high degree of precision. Percutaneous vertebroplasty is a surgical procedure that was introduced for the treatment of compression fracture of the vertebrae. This procedure includes puncturing vertebrae and filling with polymethylmethacrylate (PMMA). Recent studies have shown that the procedure could provide structural reinforcement for the osteoporotic vertebrae while being minimally invasive and safe with immediate relief of pain. However, failures of treatment due to excessive PMMA volume injection have been reported as one of complications in vertebroplasty. It is believed that the control of PMMA volume is one of the most critical factors that can reduce the incidence of complications. Therefore, clinical success of vertebroplasty can be dependent on the volume of PMMA injection for a given patient. In this study, the optimal volume of PMMA injection for vertebroplasty was predicted based on the image analysis of a given patient.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.101-109
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• 2012

In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound(TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation inTRUS images using support vectors and snake-like contour is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. Gabor filter bank for extracting the texture features has been implemented. A support vector machine(SVM) for training step has been used to get each feature of prostate and nonprostate. The boundary of prostate is extracted by the snake-like contour algorithm. The results showed that this new algorithm extracted the prostate boundary with less than 9.3% relative to boundary provided manually by experts.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.619-628
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• 2022

Although face recognition and face generation have been growing in popularity, the privacy issues of using facial images in the wild have been a concurrent topic. In this paper, we propose a face editing network that can reduce privacy issues by generating face images with various properties from a small number of real face images and facial mask information. Unlike the existing methods of learning face attributes using a lot of real face images, the proposed method generates new facial images using a facial segmentation mask and texture images from five parts as styles. The images are then trained with our network to learn the styles and locations of each reference image. Once the proposed framework is trained, we can generate various face images using only a small number of real face images and segmentation information. In our extensive experiments, we show that the proposed method can not only generate new faces, but also localize facial attribute editing, despite using very few real face images.