• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.4
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• pp.295-299
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• 2016

Residual foreign objects at the secondary side (top of the tubesheet and tube support plates) of a steam generator are likely to cause a leak by causing wear in the tube. The extent of wear is significantly affected by the material, shape, and size of the foreign object, and the corrosion properties of the tube. The presence of foreign objects at the top of the tubesheet and tube support plates has been identified using remote visual inspection methods such as the foreign object search and retrieval and eddy current test (ECT). The detection of the residual foreign object at the secondary side of a steam generator has limitations that depend on the material properties and the condition of contact with the tube. In this study, which is vertical and horizontal from the upper tubesheet, the corresponding bobbin ECT signals were collected and analyzed to measure its ability to detect foreign objects.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.873-879
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• 2023

This study explored the use of artificial intelligence(AI) to detect foreign bodies in chest X-ray images. Medical imaging, especially chest X-rays, plays a crucial role in diagnosing diseases such as pneumonia and lung cancer. With the increase in imaging tests, AI has become an important tool for efficient and fast diagnosis. However, images can contain foreign objects, including everyday jewelry like buttons and bra wires, which can interfere with accurate readings. In this study, we developed an AI algorithm that accurately identifies these foreign objects and processed the National Institutes of Health chest X-ray dataset based on the YOLOv8 model. The results showed high detection performance with accuracy, precision, recall, and F1-score all close to 0.91. Despite the excellent performance of AI, the study solved the problem that foreign objects in the image can distort the reading results, emphasizing the innovative role of AI in radiology and its reliability based on accuracy, which is essential for clinical implementation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1027-1030
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• 2013

For the detection of objects in the videos, there are various ways that use the frequency transformation. In the videos, the images of objects could be changed slightly. Object detection methods using frequency transformation such as ASEF and MOSSE have the ability to renew the detection filter in order to deal with the change of object images. But these approaches are likely to fail the detection because the image changes often occur when they come out again after being hidden by other objects. What is worse, when they show up again, they appear in another place, not the original one. In this paper, a new proposal is present so that the detection can be carried out efficiently even when the images come out in other place, and the failure of the detection can be reduced.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.34-46
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• 2019

A method for detecting foreign substances in mould based on scatter grams was presented to protect moulds automatically during moulding production. This paper proposes a wavelet transform foreign detection method based on Monte Carlo analysis mechanism to identify foreign objects in the tube. We use the Monte Carlo method to evaluate the image, and obtain the width of the confidence interval by the deviation statistical gray histogram to divide the image type. In order to stabilize the performance of the algorithm, the high-frequency image and the low-frequency image are respectively drawn. By analyzing the position distribution of the pixel gray in the two images, the suspected foreign object region is obtained. The experiments demonstrate the effectiveness of our approach by evaluating the labeled data.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.510-513
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• 2016

Detecting of the object in image processing is substantial but it depends on the object itself and the environment. An object can be detected either by its shape or color. Color is an essential for pattern recognition and computer vision. It is an attractive feature because of its simplicity and its robustness to scale changes and to detect the positions of the object. Generally, color of an object depends on its characteristics of the perceiving eye and brain. Physically, objects can be said to have color because of the light leaving their surfaces. Here, we conducted experiment in the aquarium fish tank. Different color of fish robots are mimic the natural swim of fish. Unfortunately, in the underwater medium, the colors are modified by attenuation and difficult to identify the color for moving objects. We consider the fish motion as a moving object and coordinates are found at every instinct of the aquarium to detect the position of the fish robot using OpenCV color detection. In this paper, we proposed to identify the position of the fish robot by their color and use the position data to control the fish robot gathering in one point in the fish tank through serial communication using RF module. It was verified by the performance test of detecting the position of the fish robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2209-2221
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• 2023

As the supply of electric vehicles increases, research on wireless charging methods for convenience has been increasing. Because the electric vehicle wireless transmission device is installed on the ground and the electric vehicle battery is installed on the floor of the vehicle, the transmission and reception antennas are approximately 15-30 cm away, and thus strong magnetic fields are exposed during wireless charging. When a metallic foreign object is placed in the magnetic field area, an eddy current is induced to the metallic foreign object, and heat is generated, creating danger of fire and burns. Therefore, this study proposes a method to detect metallic foreign objects in the magnetic field area of a wireless electric vehicle charging system. An active detection-only coil array was used, and an LC resonance circuit was constructed for the frequency of the supply power signal. When a metallic foreign object is inserted into the charging zone, the characteristics of the resonance circuit are broken, and the magnitude and phase of the voltage signal at both ends of the capacitor are changed. It was confirmed that the proposed method has about 1.5 times more change than the method of comparing the voltage magnitude at one node.

• 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.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1284-1292
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• 2015

As visual surveillance systems become more and more common in human lives, approaches based on these systems to solve security problems in practice are boosted, especially in railway applications. In this paper, we first propose a robust snag detection algorithm and then present a railway security system by using a combination of multiple sensors and the vision based snag detection algorithm. The system aims safety at several repeatedly occurred situations including slope protection, inspection of the falling-object from bridges, and the detection of snags and foreign objects on the rail. Experiments demonstrate that the snag detection is relatively robust and the system could guarantee the security of the railway through these real-time protections and detections.

• 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 Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.