• Journal of Digital Convergence
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• v.10 no.8
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• pp.211-217
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• 2012

Conventional GrabCut algorithm is semi-automatic algorithm that user must be set rectangle window surrounds the object. This paper studied automatic object detection to solve these problem by detecting salient region based on Human Visual System. Saliency map is computed using Lab color space which is based on color opposing theory of 'red-green' and 'blue-yellow'. Then Saliency Points are computed from the boundaries of Low-Frequency region that are extracted from Saliency Map. Finally, Rectangle windows are obtained from coordinate value of Saliency Points and these windows are used in GrabCut algorithm to extract objects. Through various experiments, the proposed algorithm computing rectangle windows of salient region and extracting objects has been proved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.504-511
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• 2013

This paper proposes improved detection schemes for concealed micro-electronic devices using clustering and classification of radio frequency harmonics in order to protect intellectual property rights. In general, if a radio wave with a specific fundamental frequency is propagated from the transmitter of a classifier to a concealed object, the second and the third harmonics will be returned as the radio wave is reflected. Using this principle, we exploit the fuzzy c-means clustering and the ${\kappa}$-nearest neighbor classification for detecting diverse concealed objects. Simulation results indicate that the proposed scheme can detect electronic devices and metal devices in various learning environments by efficient classification. Thus, the proposed schemes can be utilized as an effective detection method for concealed micro-electronic device to protect intellectual property rights.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.13-20
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• 2021

In this paper, a new algorithm is proposed to estimate the damage size by combining the reflected area with the reflected position and extracting contours in proportion to the maximum value of pixels from the visible image. The cumulative summation feature vector algorithm is used to obtain the area of the reflected signal. To get the position of the reflected signal, the signal correlation algorithm is used to decompose the reflected signal from the damage. The proposed algorithm is tested and validated for composite panels. Repetitive experiments are performed and it is confirm that the proposed algorithm is reproducible. Further, it is verified that the damage size can be estimated appropriately by the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.519-526
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• 2016

As marine accidents happen frequently, it is required to establish a marine traffic monitoring system, which is designed to improve the safety and efficiency of navigation in VTS (Vessel Traffic Service). For this aim, recently, X-band marine radar is used for extracting the sea surface information and, it is necessary to retrieve wave information correctly and provide for the safe and efficient movement of vessel traffic within the VTS area. In this paper, three different current estimation algorithms including the classical least-squares (LS) fitting, a modified iterative least-square fitting routine and a normalized scalar product of variable current velocities are compared with buoy data and then, the iterative least-square method is modified to estimate wave information by improving the initial current velocity. Through several simulations with radar signals, it is shown that the proposed method is effective in retrieving the wave information compared to the conventional methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.623-624
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• 2009

본 논문에서는 신경망의 오류 역전파(Backpropagation) 학습 알고리즘을 이용한 얼굴의 정상 비정상을 인식하는 보안 시스템을 제안하였다. 제안된 시스템은 정지영상 및 동영상에서 입력된 얼굴영상을 전처리 단계에서 얼굴영역을 검출하여 $160{\times}160$ 크기의 고정 크기로 확대 및 축소 작업을 거친다. Mosaic 처리와 LaplacianEdge 처리를 거쳐 $40{\times}40$ 크기로 이진화한 정규화 데이터를 Gravity-Center 처리를 한다. 오류 역전파 학습 알고리즘으로 얼굴의 특징을 학습한 후 각종 정상 및 비정상 얼굴 데이터를 이용하여 인식률을 실험 하였다. 실험데이터는 이 분야의 공인 자료인 LFW Face Database[7] 데이터를 사용하였으며, 실험결과는 제안된 방법이 문제 해결에 적합한 접근임을 보여준다.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.446-460
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• 2022

In this paper, we propose an algorithm to improve target detection rate degradation due to direct blast in a bi-static sonar systems with high duty cycle using an adaptive filters. It is very important to suppress the direct blast in the aforementioned sonar systems because it has a fatal effect on the actual system operation. In this paper, the performance was evaluated by applying the Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms to the simulation and sea experimental data. The beam signals of the target and direct blast bearings were used as the input and desired signals, respectively. By optimizing the difference between the two signals, the direct blast is removed and only the target signal is remained. As a result of evaluating the results of the matched filter in the simulation, it was confirmed that the direct blast was removed to the noise level in both Linear Frequency Modultated (LFM) and Generalized Sinusoidal Frequency Modulated (GSFM), and in the case of GSFM, the target sidelobe decreased by more than 20 dB, thereby improving performance. In the sea experiment, it was confirmed that the LFM reduced the level of the transmitted direct wave by 10 dB, the GSFM reduced the level of the transmitted direct wave by about 4 dB, and the side lobe of the target decreased by about 4 dB, thereby improving the performance.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.427-433
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• 2022

Obstacle detection, collision recognition, and avoidance technologies are required the collision avoidance technology for UAVs. In this paper, considering collinear multiple static obstacle, we propose an obstacle detection algorithm using LiDAR and a collision recognition and avoidance algorithm based on CPA. Preprocessing is performed to remove the ground from the LiDAR measurement data before obstacle detection. And we detect and classify obstacles in the preprocessed data using the K-means clustering algorithm. Also, we estimate the absolute positions of detected obstacles using relative navigation and correct the estimated positions using a low-pass filter. For collision avoidance with the detected multiple static obstacle, we use a collision recognition and avoidance algorithm based on CPA. Information of obstacles to be avoided is updated using distance between each obstacle, and collision recognition and avoidance are performed through the updated obstacles information. Finally, through obstacle location estimation, collision recognition, and collision avoidance result analysis in the Gazebo simulation environment, we verified that collision avoidance is performed successfully.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.456-463
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• 2021

In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.627-635
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• 2017

Modern warfare is gradually changing into a network war, and information electronic warfare is also progressing. In modern war, electronic warfare is all military activity concerned with electromagnetic field use, such as signal collecting, communication monitoring, information analysis, and electronic attack. The one key function of signal collecting for enemy signal analysis, direction finding, collects the signal radiated from enemy area and then calculates the enemy direction. This paper examined the Watson-Watt algorithm for an amplitude direction finding system and CVDF algorithm for phase direction finding system and analyzed the difference in the direction finding accuracy between in the clean electromagnetic field environment and in the real operating field environment of electronic warfare system. In the real field, the direction finding accuracy was affected by the reflected field from the surrounding obstacles. Therefore, this paper proposesan enhanced direction finding process for reducing the effect. The result of direction finding by applying the proposed process was enhanced above $1.24^{\circ}$ compared to the result for the existing process.

• Journal of KSNVE
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• v.7 no.2
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• pp.209-214
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• 1997

Vibration characteristics which are typical in a cracked rotor can be utilized for detection of crack. The changing trend of harmonics at the second harmonic resonant speed according to the crack depth and the unbalance orientation has been discussed. To characterize the vibration depending on crack orientation, the unbalance and gravitational responses of the cracked rotor are calculated. An algorithm for crack orientation identification is also introduced. A trial mass is attached step by step with even angle interval along a certain circumference, and then the synchronous and second horizontal harmonic compenents of vibration are measured and curve-fitted using least square method. Numerical simulations using this method show good results.