• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2349-2358
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• 1999

Object-based stereoscopic video coding scheme is presented in this paper. In conventional BMA based stereoscopic video coding for low bit rate transmission, image prediction errors such as block artifacts and mosquito phenomena are occurred. In order to reduce these errors, object based coding scheme is adopted. The proposed scheme consists of preprocessing, object extraction, and object update procedures. The preprocessing procedure extracts non-object regions having low reliability for motion and disparity estimation. This procedure prohibits extracting inaccurate objects. For the better prediction of left channel image, the disparity information is added to the object extraction. And the proposed algorithm can reduce the accumulated error through the object update procedure that detects newly emerging objects, merges objects that have the same object-disparity and object motion, and splits object which has large image prediction error. The experimental results show that the proposed algorithms improve the quality of the prediction without block artifacts and mosquito phenomena.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.591-601
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• 2002

Motion compensation is a powerful method to compress an image sequence. Its main drawback is that once an error is occurred, the error propagates through the frames. Recently, the intra update method was proposed to stop the error propagation at the expense of reduction in compression efficiency. This paper proposes an intra update method based on a rate-distortion optimization in error prone environments. The rate and the distortion are estimated using the Lagrangian optimization to select the coding mode and the quantization step size. The proposed method is applied to MPEG-4 codec, and the experimental results show that it is robust to the error such as packet losses comparing with the conventional ones.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.1-10
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• 2006

To reduce the complexity of video transcoder, transcoding techniques generally use intermediate data such as macroblock types, motion vectors, DCT coefficients, which are extracted from incoming video bitstream. In this Paper, we Propose a new adaptive INTRA update scheme utilizing the importance of each macroblock in a given frame. The importance measure is calculated from the motion vectors which are extracted from the decoding procedure of a incomming video data.'rho ratio of the macroblock to be referred by the next frame is calculated by the motion vectors of the next frame and the macroblocks to be refered higher ratio has more effect on the next frame and the followed frames. The proposed scheme can obtain transcoded bitstreams which has better image quality and more improved resilience against transmission errors.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.763-776
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• 2021

This paper introduces a method of selecting priority update areas for subdivided land cover maps by training orthoimages and serial cadastral maps in a deep learning model. For the experiment, orthoimages and serial cadastral maps were obtained from the National Spatial Data Infrastructure Portal. Based on the VGG-16 model, 51,470 images were trained on 33 subdivided classifications within the experimental area and an accuracy evaluation was conducted. The overall accuracy was 61.42%. In addition, using the differences in the classification prediction probability of the misclassified polygon and the cosine similarity that numerically expresses the similarity of the land category features with the original subdivided land cover class, the cases were classified and the areas in which the boundary setting was incorrect and in which the image itself was determined to have a problem were identified as the priority update polygons that should be checked by operators.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.705-708
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• 2005

Mobile Mapping Systems using the vehicle equipped the GPS, IMU, CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. They must provide users with the sensor data which is acquired by Mobile Mapping Systems in real-time so that users can process what they want by using the latest data. But it' s not an easy process because the amount of sensor data is very large, particularly image data to be transmitted. So it is necessary to reduce the amount of image data so that it is transmitted effectively. In this study, the effective method was suggested for the compression/decompression image data using the Wavelet Transformation and Huffman Coding. This technique will be possible to transmit of the geographic information effectively such as position data, attitude data, and image data acquired by Mobile Mapping Systems in the wireless internet environment when data is transmitted in real-time.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.228-236
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• 1999

In this paper, we propose visual-based self-localization and obstacle detection algorithms for indoor mobile robots. The algorithms do not require calibration, and can be worked with only single image by using the projective invariant relationship between natural landmarks. We predefine a risk zone without obstacles for a robot, and update the image of the risk zone, which will be used to detect obstacles inside the zone by comparing the averaging image with the current image of a new risk zone. The positions of the robot and the obstacles are determined by relative positioning. The method does not require the prior information for positioning robot. The robustness and feasibility of our algorithms have been demonstrated through experiments in hallway environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.767-770
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• 2001

Edge detection is one of issues with essential importance in the area of image process. An edge in image is a boundary or contour which a significant change occurs in image intensity. In the paper, we process edge detection algorithms which are based on Potts automata. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. If Potts Automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose a Potts Automata technique for detecting edge. Based on the experimental results we discuss the advantage and efficiency.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.577-590
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• 2013

Shamir's (k,n)-threshold secret sharing scheme is not secure against cheating by attacker because the signature of participants is omitted. To prevent cheating, many schemes have been proposed, and a proactive secret sharing is one of those. The proactive secret sharing is a method to update shares in the secret sharing scheme at irregular intervals. In this paper, a proactive image secret sharing scheme over $GF(2^8)$ is proposed for the first time. For the past 30 years, Galois field operation is widely used in order to perform the efficient and secure bit operation in cryptography, and the proposed scheme with update phase of shadow image over $GF(2^8)$) at irregular intervals provides the lossless and non-compromising of secret image. To evaluate security and efficiency of images (i.e. cover and shadow images) distortion between the proposed scheme and the previous schemes, embedding capacity and PSNR are compared in experiments. The experimental results show that the performances of the embedding capacity and image distortion ratio of the proposed scheme are superior to the previous schemes.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1097-1109
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• 2023

Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

• KIISE Transactions on Computing Practices
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• v.22 no.3
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• pp.157-162
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• 2016

The limitation of a human's visual perception is considered to be 60 frames per second, This study investigated the effects of fast update rates (above 60 fps) in terms of interaction accuracy. Initial experiments showed that the interaction accuracy increased at rates faster than 60 fps. We assumed that either or both of the following two situations would cause such an effect: the user could recognize rendering rates faster than 60 fps, or the input processing rates were significant for the high accuracy. To evaluate the significance of these events, we conducted a second and third experiment. Although the display refresh rate was also fixed at 60 fps (by disabling the vertical sync), the rendered image actually differed for 60 fps and 150 fps. This research shows that faster update rate is necessary to achieve high interaction accuracy, and its limit is far over the usually considered 60 fps.