• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.1
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• pp.130-135
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• 2014

FOD(Foreign Object Debris) has the potential threat to damage aircraft during critical phases of take-off and landing roll with some objects including metal on the runway. FOD can be found anywhere on an airport's air operation areas such as runway, taxiway and apron. It can lead to catastrophic loss of life and airframe, and increased maintenance and operating costs. In this paper, we defined FOD and surveyed its riskiness and necessity of automatic FOD detection system. We compared the requirements of the environment in Korea to the FAA advisory circular. Also we analyzed operation methods of FOD detection systems already installed at some airports. Based on the surveys mentioned above, we propose hybrid type of FOD detection system considering the environment in Korea which uses millimeter wave radar, optical camera and thermal imaging camera to detect FOD efficiently. In management approach, fixed type of the system should be installed for real-time monitoring, and mobile type of the system can be used additionally.

• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• Smart Media Journal
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• v.13 no.4
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• pp.65-75
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• 2024

This paper proposes a new approach to video surveillance systems, which have become essential components in modern urban management. By utilizing blockchain and IPFS, it enhances data integrity and privacy protection. Additionally, anomaly detection and automatic video storage are enabled through object detection technology, thus improving urban safety and security. This integrated approach serves as an efficient management methodology for surveillance systems, providing city administrators and citizens with a safer and more effective monitoring environment.

• 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 Society for e-Business Studies
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• v.26 no.1
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• pp.93-106
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• 2021

Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.766-771
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• 2002

Automatic change detection based on the vector-to-raster comparison is hard especially in high-resolution image. This paper proposes a method to designate roads in high-resolution image in sequential manner using the information from vector map in which Hough transform is used for reliability. By its linearity, the road of urban areas in a vector map can be easily parameterized. Following some pre-processing to remove undesirable objects, we obtain the edge map of raster image. Then the edge map is transformed to a parameter space to find the selected road from vector map. The comparison is done in the parameter space to find the best matching. The set of parameters of a road from vector map is treated as the constraints to do matching. After designating the road, we may overlay it on the raster image for precise monitoring. The results can be used for detection of changes in road object in a semi-automatic fashion.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.638-642
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• 2017

FOD is a generic term for substances with potential threats that can pose a fatal risk to aircraft. Therefore, FOD should be noted in all areas of the airport. Especially, the method of detecting and collecting FOD in runway and aircraft movements is very low efficiency and economical efficiency of airport operation, so it is essential to develop FOD automatic detection system suitable for domestic environment. As part of the aviation safety technology development project, the development of an automatic detection system for foreign matter in the moving area of the aircraft inside the airport is underway. In this paper, it is confirmed that EO / IR camera is used for detection of foreign objects at Taean Airfield of Hanseo University. EO camera is used during the day and IR camera is used at night.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1011-1019
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• 2005

In this paper, Ubiquitous Home Mess-Cleanup Robot(UHMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of tile self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulate,, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and UHMR. Finally, the good performance of the designed UHMR is confirmed through the results of the mess clean-up and arrangement.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1612-1616
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• 2005

In this paper, a Home Mess-Cleanup Robot(HMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of the self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulator, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and HMR. Finally, the good performance of the designed HMR is confirmed through the results of the mess clean-up and arrangement.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.395-401
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• 1993

The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurement of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easiliy illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is () in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed qutomatic inspection system can be applied in real situation.