• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.449-452
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• 2009

The vision of u-City is an implementation of ubiquitous environments that makes anybody to be able to access the source of information and knowledge in anywhere and anytime with any methods. It is necessary to study the law and institution of u-City about a role of the government and local governments to have a new growth power. We need to improve the related law and institution with standardization of u-City service to regulate and coordinate diversity of main organ and business area. In this paper, we select service modes to consider the priority order of service and suggest a reform measure of law and institution classified by service models

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.689-695
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• 2004

This paper presents a robot system that combines computer network and an autonomous mobile robot where RTOS is installed. We propose a wireless communication protocol, and also implement it on the RTOS of the robot system. Main controller of the robot processes the control program as a task type in the real-time operating system. Peripheral devices are driven by the device driver functions with the dependency of the hardware. Because the client and server program was implemented to support the multi-platforms by Java SDK and Java JMF, it is easy to analyze programs, maintain system, and correct the errors in the system. End-user can control a robot with a vision showing remote sight over the Internet in real time, and the robot is moved keeping away from the obstacles by itself and command of the server received from end-user at the local client.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.158-163
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• 2006

The study of this study is to suggest the advanced vision of LRT O&M through comparing the domestic and japanese. Currently local government attract a private capital to construct the LRT competitively. It was investigated the O&M field participation of Light Rail Transit by the Seoul metro which operates Seoul subway 1,2,3,4 lines at this time. But, according to the restricted operation experiences in domestic, Japanese companies which operates a Light Rail Transit in Japan were analysed using several statistics. It were compared with operation plan of domestic execution design phase of representative 4 lines. The analysis gives us some points in common and suggestions that are very important and prerequisite for advancing seoul metro into LRT O&M business.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.294-296
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• 1996

The process of detecting edge in an image is an important component of many Pattern Recognition and Computer Vision applications. In many practical cases, there exist blurred images due to defocussing, movement of an object and so on. In addition, local perturbation noise can be added to the images. We propose the edge detection technique in blurred and noisy image. For this, we use Fuzzy pyramid linking mothod to remove noise and enhance the edge in images. We develop contrast intensifier using the concept of Fuzzy sets as a postprocessing.

• Smart Media Journal
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• v.2 no.1
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• pp.31-36
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• 2013

A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.

• Journal of Korean Society of Rural Planning
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• v.16 no.1
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• pp.35-47
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• 2010

With the cognition of the problems on propulsion system of rural development program, the requirement for accurate diagnosis of the problems and for reform scheme is increasing. This study was performed to solve the above requirement especially on the level of a local government, Chungnam province as an instance. For accurate diagnosis of the problems, the present situation of propulsion system, i.e. organization and governance, planning and policy making, implementation and supervision of rural development program was investigated, and the cognition of public officials and specialists was surveyed. From the study, it showed that the problems of propulsion system for rural development program in Chungnam province are duplication of work sphere among departments, formal administration of governance, an absence of long-term plan with vision and strategy, and absence of department in charge of comprehensive supervision and so on. As a result of the study 9 reform schemes to solve the problems were suggested.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.483-500
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• 2007

Emerging sensor-based structural health monitoring (SHM) technology can play an important role in inspecting and securing the safety of aging civil infrastructure, a worldwide problem. However, implementation of SHM in civil infrastructure faces a significant challenge due to the lack of suitable sensors and reliable methods for interpreting sensor data. This paper reviews recent efforts and advances made in addressing this challenge, with example sensor hardware and software developed in the author's research center. It is proposed to integrate real-time continuous monitoring using on structure sensors for global structural integrity evaluation with targeted NDE inspection for local damage assessment.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.54-59
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• 2019

The parametrization of the surface plays an important role in the 3D computer graphics and computer vision. Especially, it is essential in 3D mesh editing that manipulates the position of 3D objects on a computer monitor. Because computer monitors are two-dimensional, while vertices of objects that actually want to change are in a three-dimensional virtual space. In this study, we propose a new type of parametrization method that takes advantage of the special properties of circles that are common to local parameterization. Experimental results show that our parameterization method is more efficient in terms of time and space than the standard parameterization method that was designed by Floater et al.

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.432-442
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• 2019

Most current human action recognition methods based on deep learning methods. It is required, however, a very high computational cost. In this paper, we propose an action change detection method to reduce repetitive human action recognition tasks. In reality, simple actions are often repeated and it is time consuming process to apply high cost action recognition methods on repeated actions. The proposed method decides whether action has changed. The action recognition is executed only when it has detected action change. The action change detection process is as follows. First, extract the number of non-zero pixel from motion history image and generate one-dimensional time-series data. Second, detecting action change by comparison of difference between current time trend and local extremum of time-series data and threshold. Experiments on the proposed method achieved 89% balanced accuracy on action change data and 61% reduced action recognition repetition.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.453-461
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• 2021

Many deep learning approaches have been studied for image classification in computer vision. However, there are not enough data to generate accurate models in medical fields, and many datasets are not annotated. This study presents a new method that can use both unlabeled and labeled data. The proposed method is applied to classify cervix images into normal versus cancerous, and we demonstrate the results. First, we use a patch self-supervised learning for training the global context of the image using an unlabeled image dataset. Second, we generate a classifier model by using the transferred knowledge from self-supervised learning. We also apply attention learning to capture the local features of the image. The combined method provides better performance than state-of-the-art approaches in accuracy and sensitivity.