• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1456-1461
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• 2003

Recently, the quantity of using information go on increasing geometric-progression. At the same time, the management of information is effected on the most organization's effective operation so that many user call for the powerful equipment which expound. access more information. As information searching technology is concentrated about the object of information based on a letter mainly, an effective searching technology for the object of multimedia such as a still image, a video and a sound must be studied. As a monitor of computer is 2-D, it difficult for one to grasp the whole aspect at a look glance like a library. Accordingly, some condition is necessary. First, it acquired the virtual video, turning a camera around by 30 degrees with a camera of 15mm lens, giving a warping and distortion. Second, it improved the books for user to search easily, adding to the video in existing books information system. The original text suggests some way which can embody the video searching technology under the base of personal computer.

• Journal of radiological science and technology
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• v.28 no.1
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• pp.19-24
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• 2005

The purpose of this study was to design and implement a useful annotation-based Radiological image retrieval system to accurately determine on education and image information for Radiological technologists. For better retrieval performance based on large image databases, we presented an indexing technique that integrated $B^+-tree$ proposed by Bayer for indexing simple attributes and inverted file structure for text medical keywords acquired from additional description information about Radiological images. In our results, we implemented proposed retrieval system with Delphi under Windows XP environment. End users, Radiological technologists, are able to store simple attributes information such as doctor name, operator name, body parts, disease and so on, additional text-based description information, and Radiological image itself as well as to retrieve wanted results by using simple attributes and text keywords from large image databases by graphic user interface. Consequently proposed system can be used for effective clinical decision on Radiological image, reduction of education time by organizing the knowledge, and well organized education in the clinical fields. In addition, It can be expected to develop as decision support system by constructing web-based integrated imaging system included general image and special contrast image for the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4614-4622
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• 2010

Urban Skyline is strongly influenced by high-rise buildings. It is changed and becoming over time and is formed by the human choice. This study does an analysis of the foreign urban skyline managements in three aspects: criteria and control, operation and deliberation, and citizen participation and inducement. It draws common characteristics of foreign cases; preparing rational and premeditated building height control in the aspect of district, transformation from height restrictions of individual building to height standards in the aspect of urban landscape, devising efficient design review and citizen participation methods, and administrative processing for an integrated building height management. It also suggests policy implications for preparing both comprehensive and systematic building height standards in the aspect of district to create a desirable city image and urban skyline.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.35-43
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• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.475-483
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• 2018

Most of logistics system has difficulties in transportation logistics tracking due to problems in real world such as discordance between logistics information and logistics flow. For the solution to these problems, through case study about corporation, suppliers that transport order items in shopping mall, we retain traceability of order items through accordance between logistics and information flow and derive transportation logistics tracking model. Through literature review, we selected permissioned public block chain model as reference model which is suitable for transportation logistics tracking model. We compared, analyzed and evaluated using centralized model and block chain as application model for transportation logistics tracking model. In this paper we proposed transportation logistics tracking model which integrated with logistics system in real world. It can be utilized for tracking and detection model and also as a tool for marketing.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.29-37
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• 2021

In this paper, we propose a deep learning-based retinal vessel segmentation model for handling multi-scale information of fundus images. we integrate the selective kernel convolution into U-Net-based convolutional neural network. The proposed model extracts and segment features information with various shapes and sizes of retinal blood vessels, which is important information for diagnosing eye-related diseases from fundus images. The proposed model consists of standard convolutions and selective kernel convolutions. While the standard convolutional layer extracts information through the same size kernel size, The selective kernel convolution extracts information from branches with various kernel sizes and combines them by adaptively adjusting them through split-attention. To evaluate the performance of the proposed model, we used the DRIVE and CHASE DB1 datasets and the proposed model showed F1 score of 82.91% and 81.71% on both datasets respectively, confirming that the proposed model is effective in segmenting retinal blood vessels.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.463-469
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• 2021

The aesthetic value of Korea is rising in various fields through the use of designs using Korean materials. Korean materials contain oriental ideas and are widely used as materials for design development due to the uniqueness of its form. The purpose of this study is to present basic data of nail art design differentiated nail art designs required at the nail art industry site by producing nail works using Korean materials. Accordingly, We proceeded on the basis of theoretical consideration and empirical research for the development of nail art design, a field of beauty in this study, and made a Korean and unique nail art design work using the Four Gracious Plants. For this purpose, we considered theoretically the characteristics of nail art and the Gracious Plants, and made nail art design works derived from empirical research. The work was analyzed by color, texture, and design elements of form. Therefore, the mixed method of Nail Art and the Gracious Plants, which is the core of this study, is considered to be meaningful in laying the foundation for creative nail art design development.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.519-528
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• 2022

The purpose of the study was to further investigate the direction for one-person experience design based on visual shift due to the isolation one has experienced after the COVID-19 and the factors regarding it. The study involves eight female participants who are in their twenties via digital platform. The participants were instructed to choose digital image similar to COVID-19 and to write down facts based upon the image and the researcher will look into the result microscopically. The researchers found that the isolation factors include decreased face-to-face communication, reliance on social media, heavy usage of OTT platform, limited outdoor occasion and activity, limitation of untact technology and education program, fear over the pandemic and so on. The study has shown that the one-person experience design should be heading in a direction where it adopts space design that can crossover online and offline world, digital complex design to embody realness as well as the communication design to regain the relationships with others.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.381-388
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• 2022

In instance segmentation, Mask-RCNN is mostly used as a base model. Increasing the performance of Mask-RCNN is meaningful because it affects the performance of the derived model. Mask-RCNN has a transform module for unifying size of input images. In this paper, to improve the Mask-RCNN, we apply deep-learning-based ASSR to the resizing part in the transform module and inject calculated scale information into the model using IM(Integration Module). The proposed IM improves instance segmentation performance by 2.5 AP higher than Mask-RCNN in the COCO dataset, and in the periment for optimizing the IM location, the best performance was shown when it was located in the 'Top' before FPN and backbone were combined. Therefore, the proposed method can improve the performance of models using Mask-RCNN as a base model.