• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.223-236
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• 2012

We develop a video processing method that allows the more advanced human perception oriented video coding. The proposed method necessarily reflects all influences by the rate-distortion based optimization and the human visual perception that is affected by the visual saliency, the limited space-time resolution and the regional moving history. For reflecting the human perceptual effects, we devise an online moving pattern classifier using the Hedge algorithm. Then, we embed the existing visual saliency into the proposed moving patterns so as to establish a human visual perception model. In order to realize the proposed human visual perception model, we extend the conventional foveation filtering method. Compared to the conventional foveation filter only smoothing less stimulus video signals, the developed foveation filter can locally smooth and enhance signals according to the human visual perception without causing any artifacts. Due to signal enhancement, the developed foveation filter more efficiently transfers the bandwidth saved at smoothed signals to the enhanced signals. Performance evaluation verifies that the proposed video processing method satisfies the overall video quality, while improving the perceptual quality by 12%~44%.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.510-514
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• 2009

This program was developed in Visual C + +, the Windows operating system has security features within the files and directories. File and directory security, encryption / decryption operations yirueojimyeo file security can be round, to know the value of the key and security password I need to know the directory is designed to be decrypted. In addition, ECB, CBC algorithm and 3DES, SEED algorithms and methods, and encryption. De0 can not run that created the file extension, as has been developed to allow for double security.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1055-1058
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is the use of different model (CAD model etc.) known a priori. Also fusion or multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Voting-based fusion of cues is adapted. In voting. a very simple or no model is used for fusion. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters. namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Journal of Information Display
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• v.13 no.3
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• pp.101-106
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• 2012

This study was conducted to enhance the cubic effect by representing an image with a sense of three-dimensional (3D) depth, using chromostereopsis, among the characteristics of human visual perception. An algorithm that enhances the cubic effect, based on the theory that the cubic effect of the chromostereoptic effect and the chromostereoptic reversal effect depends on the lightness of the background, classifies the layers of the 3D image input into the foreground, middle, and background layers according to the depth of the image input. It suits the characteristics of human visual perception because it controls the color factor that was adaptively detected through experiments on each layer; and it can achieve an enhanced cubic effect that is suitable for the characteristics of the image input.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.162-171
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• 1999

The most important part in automated transport systems is steering control for lane keeping Most of systems developed so far have used the visual information for steering control. In this study, the steering control algorithm based on visual servoing has been developed and tested by applying it on Radio Controlled(R/C) model car equipped with one CCD camera. We also demonstrated the feasibility of using it as a pre-test car before the real car experiment in developing automated vehicles. In order to solve the problem of the limited spave and load of a model car, remote-brained approach has been taken. For steering control of a model car, the PD controller which uses the look ahead offset to generate control input has been implemented and the characteristics of the controller has been explained in view of kinematics. Some experimental results have been also illustrated so as to show the control performance and stability.

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.417-423
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• 2019

This paper presents an evaluation system to determine the completeness of a space map obtained by a visual SLAM(Simultaneous Localization And Mapping) algorithm. The proposed system consists of three parts. First, the proposed system detects the occurrence of loop closing to confirm that users acquired the information from all directions. Thereafter, the acquired map is divided with regular intervals and is verified whether each area has enough map points to successfully estimate users' position. Finally, to check the effectiveness of each map point, the system checks whether the map points are identifiable even at the location where there is a large distance difference from the acquisition position. Experimental results show that space maps whose completeness is proven by the proposed system has higher stability and accuracy in terms of position estimation than other maps that are not proven.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.238-244
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• 2021

Image mosaicking is a common and useful technique to visualize a global map by stitching a large number of local images obtained from visual surveys in underwater environments. In particular, visual inspection of underwater structures using underwater robots can be a potential application for image mosaicking. Feature-based pairwise image registration is a commonly employed process in most image mosaicking algorithms to estimate visual odometry information between compared images. However, visual features are not always uniformly distributed on the surface of underwater structures, and thus the performance of image registration can vary significantly, which results in unnecessary computations in image matching for poor-conditioned image pairs. This study proposes a pairwise registrability measure to select informative image pairs and to improve the overall computational efficiency of underwater image mosaicking algorithms. The validity and effectiveness of the image mosaicking algorithm considering the pairwise registrability are demonstrated using an experimental dataset obtained with a full-scale ship in a real sea environment.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.265-278
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• 1991

The purpose of this study is to suggest objective basic data for the design and management of the national park roadside slopes through the quantitative analysis of the visual quality included in the physical environment of the Chi-ri national park, for this, visual volumes of physical elements have been evaluated by using the mesh analysis, spatial images structure of physical elements have been analyzed by factor analysis algorithm, and degree of visual quality have been measured mainly by questionnaires. Result of this thesis can be summarized as fallows. Visual volumes of the naked, rock, ground cover of seed spray, and artificial planting are found to be the main factor determining the visual quality. Factors covering the spatial image of the national park roadside slopes landscape have been found to be the overall synthetic evaluation, spatial, appeal, physical, openness and dignity factors such as the overall the spatial, physical and openness yield high factor scores. As for the factors determining the degree of visual quality of the roadside slopes, variables such as the summit, the constructions management, harmony of landscape, visual stability of roadside slopes, suitable artificial planting and suitable constructions.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.109-117
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• 2009

Identity recognition in real environment with a reliable mode is a key issue in human computer interaction (HCI). In this paper, we present a robust person identification system considering score-based optimal reliability measure of audio-visual modalities. We propose an extension of the modified reliability function by introducing optimizing parameters for both of audio and visual modalities. For degradation of visual signals, we have applied JPEG compression to test images. In addition, for creating mismatch in between enrollment and test session, acoustic Babble noises and artificial illumination have been added to test audio and visual signals, respectively. Local PCA has been used on both modalities to reduce the dimension of feature vector. We have applied a swarm intelligence algorithm, i.e., particle swarm optimization for optimizing the modified convection function's optimizing parameters. The overall person identification experiments are performed using VidTimit DB. Experimental results show that our proposed optimal reliability measures have effectively enhanced the identification accuracy of 7.73% and 8.18% at different illumination direction to visual signal and consequent Babble noises to audio signal, respectively, in comparison with the best classifier system in the fusion system and maintained the modality reliability statistics in terms of its performance; it thus verified the consistency of the proposed extension.