• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.41-48
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• 2013

A positioning technique using the augmentation system has been researched to improve the accuracy. The network RTK is the precise positioning technique using carrier phase correction data from reference stations and is constantly being researched. The study for the system accuracy has been performed but system integrity research has not been done as much as system accuracy. In this paper, we presented the anomaly detection algorithm by satellite system and the diagnosis algorithm to a basic research in the integrity on network RTK. And the presented algorithms are verified on the DL-V3 dual-frequency receiver and the simulated error scenario using the GSS7700.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.87-94
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• 2008

In this paper, we propose a new vision-based fire detection method for a real-life application. Most previous vision-based methods using color information and temporal variation of pixel produce frequent false alarms because they used a lot of heuristic features. Furthermore there is also computation delay for accurate fire detection. To overcome these problems, we first detected candidated fire regions by using background modeling and color model of fire. Then we made probabilistic models of fire by using a fact that fire pixel values of consecutive frames are changed constantly and applied them to a Bayesian Network. In this paper we used two level Bayesian network, which contains the intermediate nodes and uses four skewnesses for evidence at each node. Skewness of R normalized with intensity and skewnesses of three high frequency components obtained through wavelet transform. The proposed system has been successfully applied to many fire detection tasks in real world environment and distinguishes fire from moving objects having fire color.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.641-650
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• 2005

In this parer, curve stopping function based on the CT number of lung parenchyma from CT lung images is proposed to detect lung region in replacement of conventional edge indication function in geodesic active contour model. We showed that the proposed method was able to detect lung region more effectively than conventional method by applying three kinds of measurement numerically. And, we verified the effectiveness of proposed method visually by observing the detection Procedure on actual CT images. Because lung parenchyma region could be precisely detected from actual EBCT (electron beam computer tomography) lung images, we were sure that the Proposed method could aid to early diagnosis of lung disease and local abnormality of function.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1172-1178
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• 2018

A system that control computer presentations by using the hand motion recognition and identification is proposed. The system recognizes and identifies various types of motion in hand motion, controlls the presentation without additional control devices. To recognize hand movements, it performs a face and hand region detection. Facial area is detected using Haar classifier and hand region is extracted according to skin color information on HSV color model. The face area is used to determine the beginning and end of hand gestures, the size and direction of motion. It recognizes various hand gestures and uses them to control computer presentations according to the hand motion identification rules that are proposed and set horizontal and vertical axes from the face area. It is confirmed that 97.2% recognition rate is obtained in about 1200 hand motion recognition experiments and the proposed algorithm is valid in presentation control.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.521-526
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• 2005

In this Paper, we propose a keyword spotting system as an alternative to searching system for poor quality Korean document images and compare the Proposed system with an OCR-based document retrieval system. The system is composed of character segmentation, feature extraction for the query keyword, and word-to-word matching. In the character segmentation step, we propose an effective method to remove the connectivity between adjacent characters and a character segmentation method by making the variance of character widths minimum. In the query creation step, feature vector for the query is constructed by a combination of a character model by typeface. In the matching step, word-to-word matching is applied base on a character-to-character matching. We demonstrated that the proposed keyword spotting system is more efficient than the OCR-based one to search a keyword on the Korean document images, especially when the quality of documents is quite poor and point size is small.

• Convergence Security Journal
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• v.20 no.3
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• pp.53-60
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• 2020

At the present stage of the fourth industrial revolution, machine learning and artificial intelligence technologies are rapidly developing, and there is a movement to apply machine learning technology in the security field. Malicious code, including new and transformed, generates an average of 390,000 a day worldwide. Statistics show that security companies ignore or miss 31 percent of alarms. As many malicious codes are generated, it is becoming difficult for humans to detect all malicious codes. As a result, research on the detection of malware and network intrusion events through machine learning is being actively conducted in academia and industry. In international conferences and journals, research on security data analysis using deep learning, a field of machine learning, is presented. have. However, these papers focus on detection accuracy and modify several parameters to improve detection accuracy but do not consider the ratio of dataset. Therefore, this paper aims to reduce the cost and resources of many machine learning research by finding the ratio of dataset that can derive the highest detection accuracy in CNN Mobile net-based malware detection model.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.149-156
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• 2003

In the latest medical world, the attempt of reconstructing anatomical human body system using computer graphics technology awakes people's interests. Actually, this trial has been made in dentistry too. There are a lot of practicable technology fields using computer graphics in dentistry For example, 3D visualization and measurement of dental data, detection of implant location, surface reconstruction for restoring artificial teeth in prostheses and relocation of teeth in orthodontics can be applied. In this paper, we propose methods for definitely detecting the geometric features of teeth such as cusp, ridge, fissure and pit, which have been used as most important characteristics in dental applications. The proposed methods are based on the approximate curvatures that are measured on a 3D tooth model made by scanning an impression. We also give examples of the geometric features detected by using the proposed methods. Comparing to other traditional methods visually, the methods are very useful in detecting more accurate geometric features.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.50-61
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• 1999

\In this paper, we consider the optimal scheduling of detection and tracking parameters in phased array radars to minimize the radar energy required for track maintenance in a cluttered environment. We develop a mathematical model of target detection induced by a search process in phased array radars. In the mathematical development, we take into account the effect of unwanted measurements that may have originated from clutter or false alarms in the detection process. We use and analytic approximation of the modified Riccati equation of the probabilistic data association (PDA) filter to take into account the effect of clutter interference in tracking. Based on the search process and the tracking models, we formulate the optimal scheduling problem into a nonlinear optimal control problem. We solve a constrained nonlinear optimization problem to obtain the solution of the optimal control problem.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.27-37
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• 2004

The detection of foreground objects in a projection display using color information can be hard due to changing lighting conditions and complex backgrounds. Accordingly, the current paper proposes a foreground object detection method using color information that is obtained from the input image to the Projector and an image captured by a camera above the projection display. After pixel correspondences between the two images are found by calibrating the geometry distortion and color distortion, the natural color variations are estimated for the projection display. Then, any pixel that has another variation not resulting from natural geometry or color distortion is considered a part of foreground objects, because a foreground object in a projection display changes the values of pixels. As shown by experimental results, the proposed foreground detection method is applicable to an interactive projection display system such as the DigitalDesk

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.21-30
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• 2005

In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.