• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.346-353
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• 2013

The dominant trend in software development is the globalisation of the software industry. This development is faced with diverse problems, which require solution by the adoption of new processes and development techniques. eXtreme Programming (known as XP) is one methodology which is now at the leading edge of software development. This recent trend in XP allows organisation members to cooperate towards the development of new software independently of the existing developers. This is achieved functionally between the members by the development of distributed pair programming, this is not IDE plug-in shape of text, simple screen sharing or chatting function based.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.163-167
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• 2018

Probabilistic approach is applied to the experiment of Probability Density Function to get the information. Especially this method will be useful to make the montage to compare similarity. But in the case of art painting, it is more difficult than montage image. In this case, we should study the habit of painter with characteristic point in the paintings. Especially we will study characteristic point in the oil paintings to decide truth or falsehood in this paper.

• Advances in aircraft and spacecraft science
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• v.11 no.1
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• pp.33-53
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• 2024

This paper presents a comprehensive investigation into the optimization of Flight Management Systems (FMS) with a particular emphasis on data processing efficiency by conducting a comparative study with conventional methods to edge-computing technology. The objective of this research is twofold. Firstly, it evaluates the performance of FMS navigation systems using conventional and edge computing methodologies. Secondly, it aims to extend the boundaries of knowledge in edge-computing technology by conducting a rigorous analysis of terrain data and its implications on flight path optimization along with communication with ground stations. The study employs a combination of simulation-based experimentation and algorithmic computations. Through strategic intervals along the flight path, critical parameters such as distance, altitude profiles, and flight path angles are dynamically assessed. Additionally, edge computing techniques enhance data processing speeds, ensuring adaptability to various scenarios. This paper challenges existing paradigms in flight management and opens avenues for further research in integrating edge computing within aviation technology. The findings presented herein carry significant implications for the aviation industry, ranging from improved operational efficiency to heightened safety measures.

• Korean Journal of Artificial Intelligence
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• v.12 no.3
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• pp.9-15
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• 2024

This paper addresses the critical need for quadcopters in GPS-denied indoor environments by proposing a novel attitude control mechanism that enables autonomous navigation without external guidance. Utilizing AR marker detection integrated with a dual PID controller algorithm, this system ensures accurate maneuvering and positioning of the quadcopter by compensating for the absence of GPS, a common limitation in indoor settings. This capability is paramount in environments where traditional navigation aids are ineffective, necessitating the use of quadcopters equipped with advanced sensors and control systems. The actual position and location of the quadcopter is achieved by AR marker detection technique with the image processing system. Moreover, in order to enhance the reliability of the attitude PID control, the dual closed loop control feedback PID control with dual update periods is suggested. With AR marker detection technique and autonomous attitude control, the proposed quadcopter system decreases the need of additional sensor and manual manipulation. The experimental results are demonstrated that the quadrotor's autonomous attitude control and operation with the dual closed loop control feedback PID controller with hierarchical (inner-loop and outer-loop) command update period is successfully performed under the non-GPS aided indoor environment and it enhanced the reliability of the attitude and the position PID controllers within 17 seconds. Therefore, it is concluded that the proposed attitude control mechanism is very suitable to GPS-denied indoor environments, which enables a quadcopter to autonomously navigate and hover without external guidance or control.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.515-521
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• 2019

The C-ITS requires the lane level positioning of the vehicle in the land transportation environment, and it is most effective to utilize the global navigation satellite system. In the precision positioning system based on satellite navigation, the evaluation of dynamic environment of lane level positioning performance should be accompanied and the evaluation system configuration should be preceded. In addition, performance analysis must be performed according to various environments that change according to traffic or road conditions in a dynamic environment. In this paper, we describe with the performance of traffic and road environment through the evaluation system of lane positioning precision positioning user system based on satellite navigation system. The numerical performance evaluation was carried out based on the data collected by carrying out the actual driving. The performance evaluation by the actual driving trajectory and driving image comparison was performed to derive and analyse evaluation results of positioning performance according to driving condition.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.118-125
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• 2016

This study evaluates the performance of image to patient registration algorithm by using stereo vision and CT image for facial region surgical navigation. For the process of image to patient registration, feature extraction and 3D coordinate calculation are conducted, and then 3D CT image to 3D coordinate registration is conducted. Of the five combinations that can be generated by using three facial feature extraction methods and three registration methods on stereo vision image, this study evaluates the one with the highest registration accuracy. In addition, image to patient registration accuracy was compared by changing the facial rotation angle. As a result of the experiment, it turned out that when the facial rotation angle is within 20 degrees, registration using Active Appearance Model and Pseudo Inverse Matching has the highest accuracy, and when the facial rotation angle is over 20 degrees, registration using Speeded Up Robust Features and Iterative Closest Point has the highest accuracy. These results indicate that, Active Appearance Model and Pseudo Inverse Matching methods should be used in order to reduce registration error when the facial rotation angle is within 20 degrees, and Speeded Up Robust Features and Iterative Closest Point methods should be used when the facial rotation angle is over 20 degrees.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.177-184
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• 2013

This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.27-33
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• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.2
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• pp.118-124
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• 2022

Marine environment analysis and ship motion prediction during ship navigation are important technologies for safe and economical operation of autonomous ships. As a marine environment analysis technology, there is a method of analyzing waves by measuring the sea states through images acquired based on radar(radio detection and ranging) signal. However, in the process of deriving marine environment information from radar images, noises generated by external factors are included, limiting the interpretation of the marine environment. Therefore, image processing for noise removal is required. In this study, image inpainting by partial convolutional neural network model is proposed as a method to remove noises and reconstruct radar images.