• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.628-631
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any cine. We implemented a real-time surveillance system that tracks a moving person using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.565-568
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• 1998

In this paper, we implemented the electornic moving aid system for safe walking of the blind. An obstacle detecting of each sector used ultrasound and a distance measurement used time of flight. The alarm is designed to have a sound and a tactile function that can be selected on an user's convenience. This system can detect and obstacle of upward, forward, downward and optimally warn to the blind with vibration, beep sound by appling warning algorithm on object detection. Experimental testing and performance evaluation have been successfully carried out with a prototype cane, and the experiment shows the capability of the function to detect unknown objects within an assigned distance, under knees, over head height, and crushed puddles.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.317-320
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any clue. We implemented a real-time surveillance system that tracks a moving person using pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• Journal of Power System Engineering
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• v.3 no.2
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• pp.64-69
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• 1999

The paper shows a result for development of BLDC motor drive by using a resolver as position detection sensor. The developed drive use a method detecting rotor position based on HSI interrupt function of microprocessor without a specialized counting circuit. The algorithm generating three-phase PWM wave to change switching voltage and current is realized based on single chip microprocessor. The PWM generating part and position counting circuit are realized by software technique without usage of conventional analogue circuit or object-oriented chips. So the drive system become compact. The effectiveness of the developed drive is verified by experimented results of speed response for step reference input.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.12-18
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• 2020

In semiconductor manufacturing, defect detection is critical to maintain high yield. Currently, computer vision systems used in semiconductor photo lithography still have adopt to digital image processing algorithm, which often occur inspection faults due to sensitivity to external environment. Thus, we intend to handle this problem by means of using Mask R-CNN instead of digital image processing algorithm. Additionally, Mask R-CNN can be trained with image dataset pre-processed by means of the specific designed digital image filter to extract the enhanced feature map of Convolutional Neural Network (CNN). Our approach converged advantage of digital image processing and instance segmentation with deep learning yields more efficient semiconductor photo lithography inspection system than conventional system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1455-1463
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• 1995

A new automatic tracking & recognition algorithm which decides the opening & the closing states of subject's eye and isn't affected by the subject's background is proposed. And it was tested in circumstances in which subject's background was not restricted using the developed system, ATRS(Automatic Tracking & Recognition System). The significant characteristic of the ATRS is new movement detection of object that is a body in motion with accelated velocity and it doesn't need any extra hardware except a formal CCD camera and an image grabber but it works so well and so fast. The ATRS would be particularly well suited to a way of communications of patients in a hospital, who can not communicate otherwise.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1151-1158
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• 2011

Proximity magnetic sensor is able to detect the object target accurately in close range and it has been widely used in the underwater guided weapon system because there is no countermeasures from the target. In order to increase the damage of target by shock wave due to explosion of the underwater guided weapon system, the maximum detection range of the proximity magnetic sensor needs to be increased. In this paper, we describe the techniques of the optimum transmitting and receiving coils design using the Finite Element Method for the output power enhancement of the transmitter and the sensitivity improvement of the receiver. Finally, the proposed design techniques of the transmitter and the receiver were verified using a experimental setup and a prototype.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.627-637
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• 2023

As the population and income levels rise, meat consumption steadily increases annually. However, the number of farms and farmers producing meat decrease during the same period, reducing meat sufficiency. Information and Communications Technology (ICT) has begun to be applied to reduce labor and production costs of livestock farms and improve productivity. This technology can be used for rapid pregnancy diagnosis of sows; the location and size of the gestation sacs of sows are directly related to the productivity of the farm. In this study, a system proposes to determine the number of gestation sacs of sows from ultrasound images. The system used the YOLOv7-E6E model, changing the activation function from sigmoid-weighted linear unit (SiLU) to a multi-activation function (SiLU + Mish). Also, the upsampling method was modified from nearest to bicubic to improve performance. The model trained with the original model using the original data achieved mean average precision of 86.3%. When the proposed multi-activation function, upsampling, and AutoAugment were applied, the performance improved by 0.3%, 0.9%, and 0.9%, respectively. When all three proposed methods were simultaneously applied, a significant performance improvement of 3.5% to 89.8% was achieved.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.191-197
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• 2010

Many does an application and application but the image analysis of face detection considerably is difficult. In order for with effect of the illumination which is irregular in the present paper America the illumination to range evenly in the face which is detected, detects a face territory, Complemented the result which detects only the front face of existing. With LAB color illumination revisions compared in Adaboost face detection of existing and 32% was visible the face detection result which improves. Bought two images which are input and executed Glassfire label rings. Compared Area critical price and became the area of above critical value and revised from RGB smooth anger and LAB images with LCFD system algorithm. The operational conversion image which is extracted like this executed a face territory detection in the object. In order to extract the feature which is necessary to a face detection used AdaBoost algorithms. The face territory remote login with the face territory which tilts in the present paper, until Multi-view face territory detections was possible. Also relationship without high detection rate seems in direction of illumination, With only the public PC application is possible was given proof user authentication field etc.