• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.652-655
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• 2004

The geometry of satellite image captured by linear pushbroom scanner is different from that of frame camera image. Since the exterior orientation parameters for satellite image will vary scan line by scan line, the epipolar geometry of satellite image differs from that of frame camera image. As we know, 2D affine orientation for the epipolar image of linear pushbroom scanners system are well-established by using the collinearity equation (Testsu Ono, 1999). Also, another epipolar geometry of linear pushbroom scanner system is recently established by Habib(2002). He reported that the epipolar geometry of linear push broom satellite image is realized by parallel projection based on 2D affine models. Here, in this paper, we compared the Ono's method with Habib's method. In addition, we proposed a method that generates epipolar resampled images. For the experiment, IKONOS stereo images were used in generating epipolar images.

• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.50-55
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• 2006

This paper presents a scheme which scrambles and descrambles images from multiple video channels. A combined image frame is formed by concatenating the incoming frames from channels in a two dimensional array. This algorithm employs an encryption scheme on row and column numbers of the combined image frame and thereby yields an encrypted combined image. The proposed algorithm is to encrypt multiple images at a time since it recomposes images from multiple video channels yielding one by composite image, and encrypts the composite image resulting In higher security.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.155-163
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• 1999

In this paper, we propose novel scene change detection and key frame selection techniques, which use two feature images, i.e., DC and edge images, extracted directly from MPEG compressed video. For fast edge image extraction. we suggest to utilize 5 lower AC coefficients of each DCT. Based on this scheme, we present another edge image extraction technique using AC prediction. Although the former is superior to the latter in terms of visual quality, both methods all can extract important edge features well. Simulation results indicate that scene changes such as cut. fades, and dissolves can be correctly detected by using the edge energy diagram obtained from edge images and histograms from DC images. In addition. we find that our edge images are comparable to those obtained in the spatial domain while keeping much lower computational cost. And based on HVS, a key frame of each scene can also be selected. In comparison with an existing method using optical flow. our scheme can select semantic key frames because we only use the above edge and DC images.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.47-53
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• 2001

Real-time multimedia transmit services like internet broadcasting, web-based education, chatting, conference, circumference observation etc. by using internet are given a great deal of weight on most recently internet services. In these way, various internet services are presented and there applications are also gradually spreaded because of improvement MPEG and streaming processing techniques. But currently internet service is a development of system which has independent function of above services. And a research and development of system which have a multipurpose internet service are insufficiency. In this paper, we design and develop system(RealCam SUN A/V) for transmitting images and voices based on MPEG4 streaming. As a result of our research, it made possible to transmit images with 15 frame/sec in 160×120 frame size at 56Kbps and 30 frame/sec in 640×480 frame size at 512Kbps. And also we can apply this system as multipurpose function to circumference observation and internet broadcasting etc., by transmitting voices, images and control signal simultaneously.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.650-652
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• 2022

Frame rate up-conversion (FRUC) algorithm is an image interpolation technology that improves the frame rate of moving pictures. This solves problems such as screen shake or blurry motion caused by low frame rate video in high-definition digital video systems, and provides viewers with a more free and smooth visual experience. In this paper, we propose a video compression technique using deep learning-based FRUC algorithm. The proposed method compresses and transmits after excluding some images from the original video, and uses a deep learning-based interpolation method in the decoding process to restore the excluded images, thereby compressing them with high efficiency. In the experiment, the compression performance was evaluated using the decoded image and the image restored by the FRUC algorithm after encoding the video by skipping 1 or 3 pages. When 1 and 3 sheets were excluded, the average BD-rate decreased by 81.22% and 27.80%. The reason that excluding three images has lower encoding efficiency than excluding one is because the PSNR of the image reconstructed by the FRUC method is low.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.297-298
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• 1998

Prototype portal imaging device (EPID) based on CCD camera, which has a $20\times20cm^2$ field of view (FOV), has been developed and then tested by acquiring phantom images for 6 MV x-ray beam. While, among the captured images, each frame suffered notorious quantum noise, the frame averaging largely enhanced the image quality against quantum noise. Over 60 frames averaging, the signal-to-noise ratio (SNR) was increased by $\sim20$ times and contrast was increased about 2 times in the skull-region of the acquired head-phantom image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1822-1828
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• 2006

A key-frame should be efficiently selected to distinguish bad information from the videos. A previous technique selecting a key-frame mostly consists of the transformation scene-centered. In the case of harmful videos containing the quaility of continuous changes, the technique makes the total rate be reduced by an unnecessary key-frame. This thesis suggests the technique selecting a key-frame, an entry of the distinguishing system by using the quality of changes between the frames. In the experiment of this technique, it was proved that over 90% of the bad information was distinguished by the selected key frame, and also time efficiency was proved by showing 68% of decrement compared to the numbers I-frame. Therefore, This technique makes the system efficient to distinguish bad information, and efficiently can contribute to the distribution of the healthy movie information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.2
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• pp.27-31
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• 2000

Thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main Part of the system is thermal camera in which a focal plane array typed sensor is introduced The sensor detects mid-range infrared spectrum or target objects and then it output generic video signal which should be processed to form a thermal image frame. A digital signal processor(DSP) in the system inputs analog to digital converted data. performs algorithms to improve the thermal images and then outputs the corrected frame data to frame buffers for NTSC encoding and for digital outputs.. To enhance the quality of the thermal images, two point correction method is applied. Figures indicate that the corrected thermal images are much improved.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.193-198
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• 2015

A large number of vision applications rely on matching keypoints across images. Pedestrian detection is under constant pressure to increase both its quality and speed. Such progress allows for new application. A higher speed enables its inclusion into large systems with extensive subsequent processing, and its deployment in computationally constrained scenarios. In this paper, we focus on improving the speed of pedestrian detection using HOG(histogram of oriented gradient) and multi frame operation which is robust to illumination changes in cluttering images. The result of our simulation indicates that the detection rate and speed of the proposed method is much faster than that of conventional HOG and differential images.