• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1589-1598
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• 1999

Conventional MSE or PSNR based methods for objective picture quality assessment of moving picture coder are not well correlated with subjective human evaluation. In recent years, the design of better objective quality assessment has attracted much intention and several picture quality metrics based on the properties of Human Visual System has been proposed. This paper proposes new metric which is appropriate for objective picture quality assessment of block based moving picture coder by considering frequency sensitivity, inter-intra channel masking and several distortion artifacts caused by block based coding. The experimental results show that the proposed method is good correlated with subjective assessment.

• International Journal of Contents
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• v.4 no.2
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• pp.24-28
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• 2008

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.55-61
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• 2017

In this paper, we propose a novel tracking method using target separation and detection that are based on discriminative correlation filter (DCF), which is studied a lot recently. 'Retainability' is one of the most important factor of tracking. There are some factors making retainability of tracking worse. Especially, fast movement and occlusion of a target frequently occur in image data, and when it happens, it would make target lost. As a result, the tracking cannot be retained. For maintaining a robust tracking, in this paper, separation of a target is used so that normal tracking is maintained even though some part of a target is occluded. The detection algorithm is executed and find new location of the target when the target gets out of tracking range due to occlusion of whole part of a target or fast movement speed of a target. A variety of experiments with various image data sets are conducted. The algorithm proposed in this paper showed better performance than other conventional algorithms when fast movement and occlusion of a target occur.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07a
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• pp.817-820
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• 2005

Legibility of electronic paper was evaluated by using the method of letter-search task and subjective visual comfort scaling. The results show that legibility depends on the illumination level, and conventional paper has a higher visual comfort rating than electronic paper although they have the similar performance in the letter-search task.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4E
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• pp.43-50
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• 1999

A fast converging coding algorithm that adaptively selects the modes of macroblocks is introduced. For a given frame, the optimal modes are selected based on the decision curves that minimize the overall distortion at a given bit rate. The method proposed in this paper is different from the conventional ones in that it does not manipulate the quantizer to meet the target bit rate but it satisfies the target bit rate by finding optimal modes of macroblocks which result consistent visual quality. Lagrange multiplier of the unconstrained cost function is controlled to trigger decision curves to generate appropriate modes to meet bit rate and the curve is obtained by utilizing simulated annealing optimization technique. The algorithm is implemented within H.261 video codec and simulation results demonstrate superior visual quality.

• ETRI Journal
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• v.31 no.2
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• pp.105-110
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• 2009

In this paper, we propose a curved projection integral imaging system to improve the horizontal and vertical viewing angles. The proposed system can be easily implemented by additional use of a large-aperture convex lens in conventional projection integral imaging. To obtain the simultaneous display of 3D images through real and virtual image fields, we propose a computer-generated pickup method based on ray optics and elemental images, which are synthesized for the proposed system. To show the feasibility of the proposed system, preliminary experiments are carried out. Experimental results indicate that our system improves the viewing angle and displays 3D images simultaneously in real and virtual image fields.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.127.4-127
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• 2001

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. A number of visual or optical technologies have been successfully applied to measure three dimensional surfaces. Especially, the shape measurement using an interferometric principle becomes a successful methodology. However, those conventional interferometric methods to measure surface profile have an inherent shortcoming, namely 2∏ ambiguity problem. The problem inevitably happens when the object to be measured has discontinuous shape due to the repetition of interferometric signal with phase period of 2∏. Therefore, in this paper, we choose as a shape measuring method, ...

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.427-430
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• 2003

This paper proposes a modified generalized side-lobe canceller with a summed adaptive filter and an adaptive compensator. A summed adaptive filter reduces computational loads and the adaptive compensator minimizes the misadjustment of the adaptive filter coefficients . Computer simulations explain the performance improvement of the proposed method and the conventional generalized side-lobe canceller.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.61-70
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• 2011

In this paper, it is realized an image filter for a noise elimination using a recurrent neural networks with fuzzy. The proposed fuzzy neural networks structure is to converge weights and the number of iteration for a certain value by using basically recurrent neural networks structure and is simplified computation and complexity of mathematics by applying the hybrid fuzzy membership function operator. In this paper, the proposed method, the recurrent neural networks applying fuzzy which is collected a certain value, has been proved improving average 0.38dB than the conventional method, the generalied recurrent neural networks, by using PSNR. Also, a result image of the proposed method was similar to the original image than a result image of the conventional method by comparing to visual images.