• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.413-414
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• 2024

영상 인식을 위한 학습 데이터 구성 단계에서 에지는 물체의 크기, 방향 등의 정보를 포함하고 있어 영상의 특징으로 사용한다. 본 논문에서는 얼굴 인식을 위하여 소벨 마스크를 사용하여 원영상과 압축영상 그리고 에지영상간의 학습에 따른 인식 정도를 파악하고자 한다. 실험결과, 원영상 그대로 인식하는 것보다 에지 영상에 의한 학습 속도에 차이가 있음을 알 수 있었다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.2
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• pp.229-236
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• 2016

For this research, the trajectory of a projectile was simulated via the multibody dynamics analysis of a self-propelled mortar. The dynamic model was composed of a mortar model and a vehicle model, and was simulated using the RecurDyn program. Interior ballistic was applied to the mortar model, and exterior ballistic was conducted by Matlab using the simulation results of the interior trajectory. Through repetitive Monte-Carlo simulations, the accuracy of the mortar was analyzed by considering variations in the aiming angle and vehicle dynamic response.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.84-90
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• 2020

As the uploading and downloading of data through the Internet is becoming more common, data including personal information are easily exposed to unauthorized users. In this study, we detect a target area in images that contain personal information, except for the background, and we protect the detected target area by using a blocking method suitable for the surrounding situation. In this method, only the target area from color image input containing personal information is segmented based on skin color. Subsequently, blurring of the corresponding area is performed in multiple stages based on the surrounding situation to effectively block the detected area, thereby protecting the personal information from being exposed. Experimental results show that the proposed method blocks the object region containing personal information 2.3% more accurately than an existing method. The proposed method is expected to be utilized in fields related to image processing, such as video security, target surveillance, and object covering.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1518-1523
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• 2012

Due to development of visual media in various industrial sectors, the importance of image processing is increasing. Among the various image processing areas, edge detection is utilized widely for various fields such as object recognition, object segmentation, the medical and other industries. Edge includes the critical factors of images like size, direction and location. Then conventional methods such as Sobel, Prewitt, Roberts and Laplacian are proposed to detect edge. However, edge detection property of these methods is declined when they are applied to the image which corrupted by AWGN(Additive White Gaussian Noise). Therefore, an algorithm using modified weighted filter is proposed in this paper and our method has excellent property on edge detection.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.7-14
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• 1996

A particle system is defined as a collection of primitive particles that together represent irregular and ever-changing objects such as smoke, clouds, waterfalls, and explosions. A particle system can be a powerful tool for modeling a deformable object's motion and change of form since it has dynamic properties with time. As an object becomes more complicated and shows more chaotic behavior, however, we need much more parameters for describing its characteristics completely. Consequently, the conventional particle system leads to difficulty in managing all of the parameters properly since one parameter can affect the others. Moreover, motion equations for representing particles' behavior are usually approximated to gain speed-ups. The inevitable errors in calculating the equations can cause an unexpected outcome. In this paper, we present a new approach of applying fuzzy contol to mage particles' motion and attributes changes over time. We also give an implementation result of a fuzzy particle system to show the feasibility of the proposed method. Applications of the system to explosions, nebulae, volcanos, and grass are presented.

• Journal of Korean Society of Disaster and Security
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• v.9 no.1
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• pp.25-32
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• 2016

Technical development have broaden human activity ranges and make human possible to defend the disasters which was undependable in the past. However, human's space activity brought a new kind of disaster to human. In the past, natural space objects was the only concern from the space, like the asteroid fallen on Chelyabinsk, Russia. But, nowadays, by the increasing number of the man-made space objects, these space kind of threat have diversified and become very real. So, nationwide safety strategy should be established to protect the people. In this paper, we suggest three points to make the decision for establishing the strategy based on the AHP analysis results.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.182-189
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• 2014

This paper proposed a framework of recognition and tracking for underwater objects using sonar images as an alternative of underwater optical camera which has the limitation of usage due to turbidity. In Part 1, a design and recognition method for 2D artificial landmark was proposed considering the practical performance of current imaging sonars. In particular, its materials are selected in order to maximize detectability based on characteristics of imaging sonar and ultrasonic waves. It has a simple and omni-directional shape which allows an easy modeling of object, and it includes region based features as identifications. Also, we proposed a real-time recognition algorithm including edge detector, Hough circle transforms, and shape matrix based recognition algorithm. The proposed methods are verified by basin tests using DIDSON.

• Journal of Space Technology and Applications
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• v.1 no.2
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• pp.149-159
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• 2021

This paper represents a reentry time prediction analysis of CZ-5B rocket-body in China, subject to analysis of the Inter-Agency Space Debris Coordination Committee Reentry (IADC) reentry test campaign conducted in May 2021. Predicting the reentry of space objects is difficult to accurately predict due to the lack of accurate physical information about target, and uncertainty in atmospheric density. Therefore, IADC conducts annual re-entry campaigns to verify analysis techniques by each agency, and the Korea Aerospace Research Institute has also participated in them since 2015. Ballistic coefficient estimation method proposed to predict target reentry time and the result confirmed the difference of 73 seconds, which confirms the accuracy of the proposed method.

• Smart Media Journal
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• v.8 no.2
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• pp.39-45
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• 2019

As deep learning has become popular, researches which can help explaining the prediction results also become important. Superpixel based multi-scale combining technique, which provides the advantage of visual pleasing by maintaining the shape of the object, has been recently proposed. Based on the principle of prediction difference, this technique computes the saliency map from the difference between the predicted result excluding the superpixel and the original predicted result. In this paper, we propose a new technique of both excluding and including super pixels. Experimental results show 3.3% improvement in IoU evaluation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.43-49
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• 2019

The wired and wireless Internet is a useful window to easily acquire various types of media data. On the other hand, the public can easily get the media data including the object to which the personal information is exposed, which is a social problem. In this paper, we propose a method to robustly detect a target object that has exposed personal information using a learning algorithm and effectively block the detected target object area. In the proposed method, only the target object containing the personal information is detected using a neural network-based learning algorithm. Then, a grid-like mosaic is created and overlapped on the target object area detected in the previous step, thereby effectively blocking the object area containing the personal information. Experimental results show that the proposed algorithm robustly detects the object area in which personal information is exposed and effectively blocks the detected area through mosaic processing. The object blocking method presented in this paper is expected to be useful in many applications related to computer vision.