• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.9-20
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• 2009

Navigation system providing route-guidance and traffic information is one of the most widely used driver-support system these days. Most of the navigation system is based on the 2D map paradigm so the information is ed and encoded from the real world. As a result it imposes a cognitive burden to the driver to interpret and translate the ed information to real world information. As a new concept of navigation system, augmented-reality navigation system (AR navigation) is suggested recently. It provides navigational guidance by imposing graphical information on real image captured by camera mounted on a vehicle in real-time. The ultimate goal of navigation system is to assist the driving task with least driving workload whether it is based on the abstracted graphic paradigm or realistic image paradigm. In this paper, we describe the comparative studies on how map navigation and AR navigation affect for driving tasks by experimental research. From the result of this research we obtained a basic knowledge about the two paradigms of navigation systems. On the basis of this knowledge, we are going to find the optimal design of navigation system supporting driving task most effectively, by analyzing characteristics of driving tasks and navigational information from the human-vehicle interface point of view.

• Journal of Advanced Navigation Technology
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• v.12 no.2
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• pp.164-169
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• 2008

This paper is using motion tracking by image segmentation to monitor intruders and to confirm based on mobile the relevant information. First, detect frame in animation that film fixed area, and make use of image subtraction between two frame that adjoin, segment fixed backing and target who move. Segmental foreground object to the edge detecting the location specified by the edge of the median estimate extracted by analyzing the motion of the intruders to monitor. When a motion is detected, the detected image is transmitted by using the W AP pull basis image transmission method on the mobile client data terminal.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1061-1067
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• 2016

Position of the vehicle for driving is essential to autonomous navigation. However, there appears GPS position error due to multipath which is occurred by tall buildings in downtown area. In this paper, GPS position error is corrected by using camera sensor and highly accurate map made with 3D-Lidar. Input image through inverse perspective mapping is converted into top-view image, and it works out map matching with the map which has intensity of 3D-Lidar. Performance comparison was conducted between this method and traditional way which does map matching with input image after conversion of map to pinhole camera image. As a result, longitudinal error declined 49% and complexity declined 90%.

• Journal of Advanced Navigation Technology
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• v.11 no.2
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• pp.163-169
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• 2007

In this paper, we propose a method of trigger pulse generation to capture the image on time by making a synchronization between the x-ray generator and digital x-ray image acquisition system. we designed a wireless trigger pulse generation circuit to make a synchronization between x-ray generator and digital image acquisition system and analysis its performance. When it starts to detect a certain level of x-ray radiation or above from the air, this method starts to generate a ACQ_START signal to indicate the timing for image acquisition starting from digital image acquisition system. Hence, when it starts to detect under certain level of x-ray signal from the air, this method starts to generate a ACC_END signal to indicate the timing for image acquisition stop from digital image acquisition system. Image acquisition is activated only this time between ACQ_START and ACQ_END signal. By doing this wireless detecting of x-ray signal from remote, we can get more accurate timing for capturing the x-ray image and any type of x-ray generator can be connected to digital image acquisition system, regards of wired protocol. This makes easy installation. We could get 3.5 line pair / mm resolution at 20 mAs of x-ray level with resolution chart. This is same or better image comparing to conventional wired result.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.672-679
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• 2011

In this paper, detection algorithm of face region based on skin color of in the TV images is proposed. In the first, reference image is set to the sampled skin color, and then the extracted of face region is candidated using the Euclidean distance between the pixels of TV image. The eye image is detected by using the mean value and standard deviation of the component forming color difference between Y and C through the conversion of RGB color into CMY color model. Detecting the lips image is calculated by utilizing Q component through the conversion of RGB color model into YIQ color space. The detection of the face region is extracted using basis of knowledge by doing logical calculation of the eye image and lips image. To testify the proposed method, some experiments are performed using front color image down loaded from TV color image. Experimental results showed that face region can be detected in both case of the irrespective location & size of the human face.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.400-407
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• 2019

In this paper, the shadow detection and reconstruction method are proposed using intrinsic image, which does not change the essential characteristics under the influence of various illuminance, and multi-scale gamma correction. The shadow detection was estimated by the pixel change information between a grayscale and an intrinsic image of the color image, and the brightness of the image were adjusted by gamma correction in the shadow restoration process. Multi-scale gamma correction is performed for each channel of a color image due to the fact that the saturation can be changed by nonlinear adjustment to individual pixel values. Multi-scale gamma values are estimated based on the information of the crossed edge between shadows and non-shadowed regions in the color image, as a result, the shadows are reconstructed by correcting different region features with multi-scale gamma values. Experimental results show that the proposed method effectively reconstructs shadows in a single natural image.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.392-399
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• 2022

With digitalization accelerated by the 4th industrial revolution, the marine traffic environment is also expected to change rapidly. The purpose of this study was to derive a new service for Aids to Navigation (AtoN) to respond to a new marine traffic environment and suggest service requirements from the perspective of the ship's operator. For this purpose, a survey of ship operators was conducted and IPA analysis was performed. Marine traffic intelligence and information services and Image-based ocean environment information services were deduced as high-priority services from the perspective of ship operators. Thus, the derived results can serve as basic data for developing new AtoN services and determining policy directions.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.376-385
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• 2023

Fishing boat capsizing accidents account for more than half of all capsize accidents. These can occur for a variety of reasons, including inexperienced operation, bad weather, and poor maintenance. Due to the size and influence of the industry, technological complexity, and regional diversity, fishing ships are relatively under-researched compared to commercial ships. This study aimed to predict the rolling motion time series of fishing boats using an image-based deep learning model. Image-based deep learning can achieve high performance by learning various patterns in a time series. Three image-based deep learning models were used for this purpose: Xception, ResNet50, and CRNN. Xception and ResNet50 are composed of 177 and 184 layers, respectively, while CRNN is composed of 22 relatively thin layers. The experimental results showed that the Xception deep learning model recorded the lowest Symmetric mean absolute percentage error(sMAPE) of 0.04291 and Root Mean Squared Error(RMSE) of 0.0198. ResNet50 and CRNN recorded an RMSE of 0.0217 and 0.022, respectively. This confirms that the models with relatively deeper layers had higher accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.673-683
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• 2010

This study investigates Terrain Aided Inertial Navigation(TAIN) which consists of Inertial Navigation System (INS) with the optical sensor for precise planetary landing. Image processing is conducted to extract the feature points between measured terrain data and on-board implemented terrain information. The navigation algorithm with Iterated Extended Kalman Filter(IEKF) can compensate for the navigation error, and provide precise navigation information compared to single INS. Simulation results are used to demonstrate the feasibility of integration to accomplish precise planetary landing. The proposed navigation approach can be implemented to the whole system coupled with guidance and control laws.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.588-593
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• 2014

Recently, the smart devices has been possessed by a large majority of the adult, and offered various personalization services. This paper proposed the lightweight Intelligent Image Security System that notice the existence of any intruder in real time at the place of requiring the security by using smart device. The proposed image security system recognized whether or not intruder exists using the difference frame on the basis of Integral Image and the dynamic background updating algorithms. The intrusion notification is achieved by using the GCM push server that send massages in the application unit of user mobile device, and the SMTP mail server which is use of e-mail standard protocol. In case of the occurrence of intruder, GCM push server send an push-massage by the private mobile device, and SMTP mail server send the intruder's photograph and intrusion time. By the convergence of the various image processing algorithms and the performance of smart device, The proposed image security system can be applied to the various Intelligent Image Security field.