• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.537-641
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• 2007

In this paper, motion analysis algorithm is presented for home surveillance of the aged who lives alone. For the first step, we acquire images from a camera. To enhance the image, we use median filtering and binarize it to reduce processing time. And then morphological operations are performed to remove small blobs and small holes. At the forth step, blobs are analysed to extracts tor foreground region. Then, motions are predicted from these images by using optical tlow technique, and the predicted motion data are refined by comparing our cardboard models so as to judge behavior pattern.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.634-636
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• 2023

Surveillance systems play a pivotal role in ensuring the safety and security of various environments, including public spaces, critical infrastructure, and private properties. However, detecting abnormal human behavior in lowlight conditions is a critical yet challenging task due to the inherent limitations of visual data acquisition in such scenarios. This paper introduces a spatiotemporal framework designed to address the unique challenges posed by low-light environments, enhancing the accuracy and efficiency of human abnormality detection in surveillance camera systems. We proposed the pre-processing using lightweight exposure correction, patched frames pose estimation, and optical flow to extract the human behavior flow through t-seconds of frames. After that, we train the estimated-action-flow into autoencoder for abnormal behavior classification to get normal loss as metrics decision for normal/abnormal behavior.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.473-481
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• 2015

The flood and environment surveillance network on riverside is a network requiring a way to efficiently manage the information from all kinds of sensors, along with an optical communication device that can deliver high-quality video information at high speed. Since on-site prompt recovery is very important especially for communication problems that occurred due to cut-off or aged network, various researches have been carried out on this. However, because the security against outside hacking or outside intrusion with illegal purposes is very important for environment surveillance network, such as the national backbone network, an efficient network maintenance and repair should be enabled while satisfying security and reliability at the same time. A characteristic of requirement is that when security is improved, the efficiency of maintenance and repair drops as they are conflicting to each other. Therefore, this research proposed a system in order to satisfy the conflicting requirement and improve security, by developing a one-way Bypass TAP and an android-based smartphone app that can enable efficient network maintenance and repair.

• Current Optics and Photonics
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• v.6 no.3
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• pp.313-322
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• 2022

Remote-sensing optical payloads, especially hyperspectral imagers, have particular issues with stray light because they often encounter high-contrast target/background conditions, such as sun glint. While developing an optical payload, we usually apply several stray-light analysis methods, including forward and backward analyses, separately or in combination, to support lens design and optomechanical design. In addition, we often characterize the stray-light response over a full field to support calibration, or when developing an algorithm to correct stray-light errors. For this purpose, we usually use forward analysis across the entire field, but this requires a tremendous amount of computational time. In this paper, we propose a sequence of forward-backward-forward analyses to more effectively investigate the through-field response of stray light, utilizing the combined advantages of the individual methods. The application is an airborne hyperspectral imager for creating hyperspectral maps from 900 to 1700 nm in a 5-nm-continuous band. With the proposed method, we have investigated the through-field response of stray light to an effective accuracy of 0.1°, while reducing computation time to 1/17^th of that for a conventional, forward-only stray-light analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.427-430
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• 2019

Object detection is applied in various field. Autonomous driving, surveillance, OCR(optical character recognition) and aerial image etc. We will look at the algorithms that are using to object detect. These algorithms are divided into two methods. The one is R-CNN algorithms [2], [5], [6] which based on region proposal. The other is YOLO [7] and SSD [8] which are one stage object detector based on regression/classification.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.194-200
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• 2020

Human detection is an important aspect in many video-based sensing and monitoring systems. Studies have been actively conducted for the automatic detection of humans in camera images, and various methods have been proposed. However, there are still problems in terms of performance and computational cost. In this paper, we describe a method for efficient human detection in the field of view of a camera, which may be static or moving, through multiple processing steps. A detection line is designated at the position where a human appears first in a sensing area, and only the one-dimensional gray pixel values of the line are monitored. If any noticeable change occurs in the detection line, corner detection and optical flow computation are performed in the vicinity of the detection line to confirm the change. When significant changes are observed in the corner numbers and optical flow vectors, the final determination of human presence in the monitoring area is performed using the Histograms of Oriented Gradients method and a Support Vector Machine. The proposed method requires processing only specific small areas of two consecutive gray images. Furthermore, this method enables operation not only in a static condition with a fixed camera, but also in a dynamic condition such as an operation using a camera attached to a moving vehicle.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.245-250
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• 2015

We have developed an optical video transmission device for HD-SDI signal transmission. The optical transmitter/receiver unit operates at DC 5 volt and small enough to be attaced near surveillance camera. They have internal voltage regulating circuits to supply 3.3V to other circuits inside the unit. The optical transmitter is composed of cable driver, laser diode driver, and laser diode. The optical receiver is composed of photodiode, limiting amp, and cable equalizer. The wavelength of the trasmitter was 1.3 um, and optical power was -5dBm, and the speed was 1.485Gbps. The receiver sensitivity was -23 dBm. We confirmed that the optical device can transmit HD-SDI video through 30 km optical fiber without any interruption.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.288-291
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• 2011

Video stabilization is an important image enhancement widely used in surveillance system in order to improve recognition performance. Most previous methods calculate inter-frame homography to estimate global motion. These methods are relatively slow and suffer from significant depth variations or multiple moving object. In this paper, we propose a fast and practical approach for video stabilization that selects the most reliable key frame as a reference frame to a current frame. We use optical flow to estimate global motion within an adaptively selected region of interest in static camera environment. Optimal global motion is found by probabilistic voting in the space of optical flow. Experiments show that our method can perform real-time video stabilization validated by stabilized images and remarkable reduction of mean color difference between stabilized frames.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.270-274
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• 2015

We suggest that HSV Color Space may be used to detect a vehicle detecting system at nighttime. It is essential that a licence plate should be extracted when a vehicle is under surveillance. To do so, a licence plate may be enlarged to certain size after the aimed vehicle is taken picture from a distance by using Pan-Tilt-Zoom Camera. Either Mean-Shift or Optical Flow Algorithm is generally used for the purpose of a vehicle detection and trace, even though those algorithms have tendency to have difficulty in detection and trace a vehicle at night. By utilizing the fact that a headlight or taillight of a vehicle stands out when an input image is converted in to HSV Color Space, we are able to achieve improvement on those algorithms for the vehicle detection and trace. In this paper, we have shown that at night, the suggested method is efficient enough to detect a vehicle 93.9% from the front and 97.7% from the back.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.529-546
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• 2009

Gauss and Laplace methods for initial orbit determination (IOD) are classical orbit determination tools and have been used very efficiently in optical satellite surveillance system. Several studies related to these two methods have been released until now. In this study, we found that the trends of IOD accuracy for different time interval between three pairs of measurement datas show unexpected results. Therefore, we checked the possible cause of these differences. In order to check various orbit types, we used most of satellite data which is able to obtain. To check the characteristics of methodology-only, we used simulated observation data. And we used real observation data for specific satellites to check the characteristics appeared when we applyed these methods to optical satellite surveillance system. As a result, we found that trends of IOD accuracy for time interval could be different because of satellite position observed.