• Proceedings of the KSRS Conference
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• v.2
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• pp.791-793
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• 2006

In the satellite camera, the incoming light source is converted to electronic analog signals by the electronic component for example CCD (Charge Coupled Device) detectors. The analog signals are amplified, biased and converted into digital signals (pixel data stream) in the video processor (A/Ds). The outputs of the A/Ds are digitally multiplexed and driven out using differential line drivers (two pairs of wires) for cross strap requirement. The MSC (Multi-Spectral Camera) in the KOMPSAT-2 which is a LEO spacecraft will be used to generate observation imagery data in two main channels. The MSC is to obtain data for high-resolution images by converting incoming light from the earth into digital stream of pixel data. The video data outputs are then MUXd, converted to 8 bit bytes, serialized and transmitted to the NUC (Non-Uniformity Correction) module by the Hotlink data transmitter. In this paper, the video data streams, the video data format, and the image data processing routine for satellite camera are described in terms of satellite camera control hardware. The advanced satellite with very high resolution requires faster and more complex image data chain than this algorithm. So, the effective change of the used image data chain and the fast video data transmission method are discussed in this paper

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.25-32
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• 2004

Purpose : The simulator is used to determine patient field and ensure the treatment field, which encompasses the required anatomy during patient normal movement such as during breathing. The latest simulator provide real time display of still, flouroscopic and digitalized image, but conventional simulator is not yet. The purpose of this study is to introduce digital image capture system(DICS) using conventional simulator and clinical case using digital captured still and flouroscopic image. Methods and materials : We connect the video signal cable to the video terminal in the back up of simulator monitor, and connect the video jack to the A/D converter. After connection between the converter jack and computer, We can acquire still image and record flouroscopic image with operating image capture program. The data created with this system can be used in patient treatment, and modified for verification by using image processing software. (j.e. photoshop, paintshop) Result : DICS was able to establish easy and economical procedure. DCIS image was helpful for simulation. DICS imaging was powerful tool in the evaluation of the department specific patient positioning. Conclusion : Because the commercialized simulator based of digital capture is very expensive, it is not easily to establish DICS simulator in the most hospital. DICS using conventional simulator enable to utilize the practical use of image equal to high cost digitalized simulator and to research many clinical cases in case of using other software program.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.347-350
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• 2011

This paper propose a statistical color model of background extraction base on Hue-Saturation-Value(HSV) color space, instead of the traditional RGB space, and shows that it provides a better use of the color information. HSV color space corresponds closely to the human perception of color and it has revealed more accuracy to distinguish shadows [3] [4]. The key feature of this segmentation method is based on processing hue component of color in HSV color space on image area. The HSV color model is used, its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination condition and shadows. Polar and linear statistical operations are used to calculate the background from the video frames. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating and shadow environments.

• Journal of the Ergonomics Society of Korea
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• v.8 no.2
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• pp.35-41
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• 1989

In this paper a new method is proposed to create 3-dimensional coordinate values from two 2- dimensional images (side and front image of objects) using image processing system and two video cameras. This method is task requiring measurements of camera lense distortion, calibrations and conversin 2-dimensional images into 3-dimensional images. This system provides 3-dimensional me- asurement error of +5mm for about 2m length objects.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.120-126
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• 2005

This paper presents the 3D wavelet based video compression system using quad-tree algorithm. The 3D wavelet based video compression system removes the temporal correlation of the input sequences using the motion compensation filter and decomposes the spatio-temporal subband using the spatial wavelet transform. The proposed system allocates the higher bit rate to the low frequency image of the 3D wavelet sequences and improves the 0.64dB PSNR performance of the reconstructed image in comparison with that of H.263. In addition to the limitation on the propagation of the motion compensation error by the 3D wavelet transform, the proposed system progressively transmits the input sequence according to the resolution and rate scalability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.49-60
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• 2008

The current VIPS are not effective in safety point of view, because they are originally developed for mimicking loop detectors. Therefore, it is important to identify vehicle trajectories in real time, because recognizing vehicle movements over a detection zone enables to identify which situations are hazardous, and what causes them to be hazardous. In order to improve limited safety functions of the current VIPS, this research has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, incident detection and conflict as well as traffic information via tracking image detectors. This system is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of various traffic situations. Experiments were conducted for measuring the cases of incident detection and abnormal vehicle trajectory with rapid lane change.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.35.4-35
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• 2001

Image detection system for road traffic data analysis is a real time detection system using image processing techniques to get the real-time traffic information which is used for traffic control and analysis. One of the most important functions in this system is to match the coordinates of real world and that of image on video camera. When there in no way to know the exact position of camera and it´s height from the object. If some points on the road of real world are known it is possible to calculate the coordinates of real world from image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.561-564
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• 2009

This paper present design and implementation of U-city infrared image surveillance system based on the digital media processor. The hardware is designed and implemented by using commercial chips such as DM642 processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a monitoring image and to monitor disaster situation such as fire. The required functions and performances are confirmed by testing of the prototype and we verified practicality of the system.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.243-250
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• 2019

In this paper, we propose a system for processing and analyzing drone image information which can be applied variously in disasters-security situation. The proposed system stores the images acquired from the drones in the server, and performs image processing and analysis according to various scenarios. According to each mission, deep-learning method is used to construct an image analysis system in the images acquired by the drone. Experiments confirm that it can be applied to traffic volume measurement, suspect and vehicle tracking, survivor identification and maritime missions.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.677-687
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• 2022

We propose a detection algorithm based on tree-structured convolutional neural networks (TsCNNs) that finds pornography, propaganda, or other inappropriate content on a social media network. The algorithm sequentially applies the typical convolutional neural network (CNN) algorithm in a tree-like structure to minimize classification errors in similar classes, and thus improves accuracy. We implemented the detection system and conducted experiments on a data set comprised of 6 ordinary classes and 11 inappropriate classes collected from the Korean military social network. Each model of the proposed algorithm was trained, and the performance was then evaluated according to the images and videos identified. Experimental results with 20,005 new images showed that the overall accuracy in image identification achieved a high-performance level of 99.51%, and the effectiveness of the algorithm reduced identification errors by the typical CNN algorithm by 64.87 %. By reducing false alarms in video identification from the domain, the TsCNNs achieved optimal performance of 98.11% when using 10 minutes frame-sampling intervals. This indicates that classification through proper sampling contributes to the reduction of computational burden and false alarms.