• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.649-657
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• 2013

Purpose: In this study, the actual situation of domestic firms vulnerable to industrial security competence will be discussed. And accordingly be discussed for effective response measures. Methods: Using a structured questionnaire by mail, fax, e-mail and fill method was used respondents. By the end of '10 R&D Center, which holds 15,247 companies(population) among the 95% level of confidence, tolerance ${\pm}3%$ p-level corporate type, sector, region extraction method stratified multi-level companies were investigated through the final 1529. Results: The average level of industrial security capabilities 43.8%(out of 100) is very weak, so urgent and positive response measures also need to be investigated sought. Conclusion: we propose the effective management framework and improvement plans to prevent illegal industrial leakage are to be made.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.603-609
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• 2018

Sudden death during sleep often occurs in different age groups. To prevent an unexpected sudden death, sleep monitoring is required. This paper presents a video analysis method to detect sudden death without using any attachable sensors. In the proposed method, a motion magnification technique detects even very subtle motion during sleep. If the magnification cannot detect motion, the proposed method readily decides on abnormal status (possibly sudden death). Experimental results on two kinds of sleep video show that motion magnification-based video analysis could be useful for discriminating sleep (with very subtle motion) from sudden death.

• Smart Structures and Systems
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• v.19 no.6
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• pp.679-694
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• 2017

The complexity, enlargement and irregularity of structures and multi-directional dynamic loads acting on the structures can lead to unexpected structural behavior, such as torsion. Continuous torsion of the structure causes unexpected changes in the structure's stress distribution, reduces the performance of the structural members, and shortens the structure's lifespan. Therefore, a method of monitoring the torsional behavior is required to ensure structural safety. Structural torsion typically occurs accompanied by displacement, but no model has yet been developed to measure this type of structural response. This research proposes a model for measuring dynamic torsional response of structure accompanied by displacement and for identifying the torsional modal parameter using vision-based displacement measurement equipment, a motion capture system (MCS). In the present model, dynamic torsional responses including pure rotation and translation displacements are measured and used to calculate the torsional angle and displacements. To apply the proposed model, vibration tests for a shear-type structure were performed. The torsional responses were obtained from measured dynamic displacements. The torsional angle and displacements obtained by the proposed model using MCS were compared with the torsional response measured using laser displacement sensors (LDSs), which have been widely used for displacement measurement. In addition, torsional modal parameters were obtained using the dynamic torsional angle and displacements obtained from the tests.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.261-269
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• 2009

In this paper we consider Internet Protocol Tele-Vision (IPTV) Service that started recently in Korea. IPTV makes it possible to watch high quality TV programs and a lot of multimedia contents with TV by way of Internet. The service providers are interested in the factors that influence the diffusion of new service such as IPTV. We therefore search the functional-attribute that would influence the acceptance of IPTV service, and propose a model for analyzing the relationship between the attributes and the intention of buying. The model is based on the extended Technology Acceptance Model (TAM). Survey results show that the significant functional attributes influencing the intention of buying are contents variety and convenience.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1536-1543
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• 2011

Video stabilization is a very important step for vision based applications in the vehicular technology because the accuracy of these applications such as obstacle distance estimation, lane detection and tracking can be affected by bumpy roads and oscillation of vehicle. Conventional methods suffer from either the zooming effect which caused by a camera movement or some motion of surrounding vehicles. In order to overcome this problem, we propose a novel video stabilization method using FOE(Focus of Expansion). When a vehicle moves, optical flow diffuses from the FOE and the FOE is equal to an epipole. If a vehicle moves with vibration, the position of the epipole in the two consecutive frames is changed by oscillation of the vehicle. Therefore, we carry out video stabilization using motion vector estimated from the amount of change of the epipoles. Experiment results show that the proposed method is more efficient than conventional methods.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.9
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• pp.831-838
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• 2014

Chip on glass (COG) bonding using anisotropic conductive film (ACF) is a key technology to assemble a driver IC onto a LCD glass panel. In this paper, an experimental investigation was conducted to investigate the correlation between contact resistance and characteristics of image taken by machine vision based inspection system. The results show that the contact resistance was strongly influenced by the contrast ratio of conductive particle rather than the number of conductive particles. Also, number of conductive particles whose contrast ratio is below 0.75 is crucial for determining the quality of the assembled samples. On the other hand, in the result of high temperature high humidity storage test, the contrast ratio of samples was increased. However, in the case of open-circuit samples after temperature humidity storage test, the number of conductive particles whose contrast ratio is above 0.75 was more than that of the closed-circuit samples.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.832-837
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.216-220
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• 2018

In this paper, we present visual sensing techniques that can be used to teach a robot using a laser pointer. The light spot of an off-the-shelf laser pointer is detected and its movement is tracked on consecutive images of a camera. The three-dimensional position of the spot is calculated using stereo cameras. The light spot on the image is detected based on its color, brightness, and shape. The detection results in a binary image, and morphological processing steps are performed on the image to refine the detection. The movement of the laser spot is measured using two methods. The first is a simple method of specifying the region of interest (ROI) centered at the current location of the light spot and finding the spot within the ROI on the next image. It is assumed that the movement of the spot is not large on two consecutive images. The second method is using a Kalman filter, which has been widely employed in trajectory estimation problems. In our simulation study of various cases, Kalman filtering shows better results mostly. However, there is a problem of fitting the system model of the filter to the pattern of the spot movement.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1264-1274
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• 2015

Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

• Journal of Mechanical Science and Technology
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• v.15 no.3
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• pp.300-308
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• 2001

Tracking of moving objects within video streams is a complex and time-consuming process. Large number of moving objects increases the time for computation of tracking the moving objects. Because of large computations, there are real-time processing problems in tracking of moving objects. Also, the change of environment causes errors in estimation of tracking information. In this paper, we present a new method for tracking of moving objects using optical flow motion analysis. Optical flow represents an important family of visual information processing techniques in computer vision. Segmenting an optical flow field into coherent motion groups and estimating each underlying motion are very challenging tasks when the optical flow field is projected from a scene of several moving objects independently. The problem is further complicated if the optical flow data are noisy and partially incorrect. Optical flow estimation based on regulation method is an iterative method, which is very sensitive to the noisy data. So we used the Combinatorial Hough Transform (CHT) and Voting Accumulation for finding the optimal constraint lines. To decrease the operation time, we used logical operations. Optical flow vectors of moving objects are extracted, and the moving information of objects is computed from the extracted optical flow vectors. The simulation results on the noisy test images show that the proposed method finds better flow vectors and more correctly estimates the moving information of objects in the real time video streams.