• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.132-137
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• 2003

This performance is motivated to develop a tracking antenna system for receive the satellite broadcasting signal in the coast sailing ship. Therefore, this system is made to small size, light weight and simple operation which is must to low cost system for popularization of small size ship and adaptive possibilities with useful on a ship in the coast using 1 axis Az-mount. The antenna mount structure is a compact size and easy operation to the Az-axis type which is operated by step motor. The antenna unit is a domestic made plate type of patch array and ship's moving detection is using the gyro sensor for ship's moving control. We are designed to algorithm, which walking is abreast for step track and ship's moving compensation. Ship's moving compensation is adapted to the closed loop control method by detection from gyro sensor. This system is consisted of micro processor, ADC, comparative amplifier, step motor driver, mount mechanism and algorithm. We have analysised the tracking performance of prototype on sailing ship board.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1130-1137
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• 2003

This performance is motivated to develop a tracking antenna system for receive the satellite broadcasting signal in the coast sailing ship. Therefore, this system is made to small size, light weight and simple operation which is must to low cost system for popularization of small size ship and adaptive possibilities with useful on a ship in the coast using 1 axis Az-mount. The antenna mount structure is a compact size and easy operation to the Az-axis type which is operated by step motor. The antenna unit is a domestic made plate type of patch array and ship's moving detection is using the gyro sensor for ship's moving control. We are designed to algorithm, which walking is abreast for step track and ship's moving compensation. Ship's moving compensation is adapted to the closed loop control method by detection from gyro sensor. This system is consisted of micro processor, ADC, comparative amplifier, step motor driver, mount mechanism and algorithm. We have analysised the tracking performance of prototype on sailing ship board.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.164-170
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• 2019

In this paper, a lane detection and tracking algorithm based on vision sensors and employing a robust filter for inner edge detection is proposed for developing a lane departure warning system (LDWS). The lateral offset value was precisely calculated by applying the proposed filter for inner edge detection in the region of interest. The proposed algorithm was subsequently compared with an existing algorithm having lateral offset-based warning alarm occurrence time, and an average error of approximately 15ms was observed. Tests were also conducted to verify whether a warning alarm is generated when a driver departs from a lane, and an average accuracy of approximately 94% was observed. Additionally, the proposed LDWS was implemented as an embedded system, mounted on a test vehicle, and was made to travel for approximately 100km for obtaining experimental results. Obtained results indicate that the average lane detection rates at day time and night time are approximately 97% and 96%, respectively. Furthermore, the processing time of the embedded system is found to be approximately 12fps.

• Smart Structures and Systems
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• v.28 no.6
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.130-138
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• 2024

High-precision 3D Object Detection is a crucial component within autonomous driving systems, with far-reaching implications for subsequent tasks like multi-object tracking and path planning. In this paper, we propose a novel approach designed to enhance the performance of 3D Object Detection, especially in heading angle estimation by employing a moving object segmentation technique. Our method starts with extracting point-wise moving labels via a process of moving object segmentation. Subsequently, these labels are integrated into the LiDAR Pointcloud data and integrated data is used as inputs for 3D Object Detection. We conducted an extensive evaluation of our approach using the KITTI-road dataset and achieved notably superior performance, particularly in terms of AOS, a pivotal metric for assessing the precision of 3D Object Detection. Our findings not only underscore the positive impact of our proposed method on the advancement of detection performance in lidar-based 3D Object Detection methods, but also suggest substantial potential in augmenting the overall perception task capabilities of autonomous driving systems.

• Fire Science and Engineering
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• v.32 no.6
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• pp.40-45
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• 2018

The omnidirectional surveillance camera uses the object detection algorithm to level the object by unit so that broadband surveillance can be performed using a fisheye lens and then, it was a field experiment with a system composed of an omnidirectional surveillance camera and a tracking (PTZ) camera. The omnidirectional surveillance camera accurately detects the moving object, displays the squarely, and tracks it in close cooperation with the tracking camera. In the field test of flame detection and temperature of the sensing camera, when the flame is detected during the auto scan, the detection camera stops and the temperature is displayed by moving the corresponding spot part to the central part of the screen. It is also possible to measure the distance of the flame from the distance of 1.5 km, which exceeds the standard of calorific value of 1 km 2,340 kcal. In the performance test of detecting the flame along the distance, it is possible to be 1.5 km in width exceeding $56cm{\times}90cm$ at a distance of 1km, and so it is also adaptable to forest fire. The system is expected to be very useful for safety such as prevention of intrinsic or surrounding fire and intrusion monitoring if it is installed in a petroleum gas storage facility or a storing place for oil in the future.

• ETRI Journal
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• v.37 no.5
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• pp.961-971
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• 2015

This paper proposes a 250 mV supply voltage digital low-dropout (LDO) regulator. The proposed LDO regulator reduces the supply voltage to 250 mV by implementing with all digital circuits in a$0.11{\mu}m$ CMOS process. The fast current tracking scheme achieves the fast settling time of the output voltage by eliminating the ringing problem. The over-voltage and under-voltage detection circuits decrease the overshoot and undershoot voltages by changing the switch array current rapidly. The switch bias circuit reduces the size of the current switch array to 1/3, which applies a forward body bias voltage at low supply voltage. The fabricated LDO regulator worked at 0.25 V to 1.2 V supply voltage. It achieved 250 mV supply voltage and 220 mV output voltage with 99.5% current efficiency and 8 mV ripple voltage at $20{\mu}A$ to $200{\mu}A$ load current.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1387-1389
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• 1987

In this paper, we describe not only extraction method of moving object by difference image but also automatic target tracking algorithm. Proposed algorithm track the moving target by the calculation of moving target's center. The results show that this algorithm can apply to practical device such as real time target tracker.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.85-94
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• 2004

Object tracking in a real time image is one of interesting subjects in computer vision and many Practical application fields during the past couple of years. But sometimes existing systems cannot find all objects by recognizing background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which is not influenced by illumination and to remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up Minimum Bounding Rectangle(MBR) using the internal point of detected object, the system tracks object through this MBR In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.454-460
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• 2020

In recent years, the rapid increases in video distribution and viewing over the Internet have increased the risk of personal information exposure. In this paper, a method is proposed to robustly identify areas in images where a person's privacy is compromised and simultaneously blocking the object area by blurring it while rapidly tracking it using a prediction algorithm. With this method, the target object area is accurately identified using artificial neural network-based learning. The detected object area is then tracked using a location prediction algorithm and is continuously blocked by blurring it. Experimental results show that the proposed method effectively blocks private areas in images by blurring them, while at the same time tracking the target objects about 2.5% more accurately than another existing method. The proposed blocking method is expected to be useful in many applications, such as protection of personal information, video security, object tracking, etc.