• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.124-131
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• 2007

This paper presents a block loss recovery technique for the image block data corrupted by transmission losses through the employment of fine directional interpolation (FDI). The proposed algorithm introduces a spatial direction vector (SDV). The SDVs are extracted from the edge information of the neighboring image data. Subsequently, the SDVs are adaptively applied to interpolate lost pixels on a pixel-by-pixel basis. This approach improves the capability to more reliably recover high-detailed contents in the corrupted block. Experimental results demonstrate that the FDI method performs better as compared to previous techniques.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.115-124
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• 2005

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the problems. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the problems. As a result. the nearest neighbor interpolation. which is the most frequently applied algorithm for the existing image interpolation algorithm. shows that the identification of a magnified image is not possible. Therefore. this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson's curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter. this study will develop an interpolation algorithm that has an excel lent improvement for the boundary of the image and continuous and flexible property by using the NURBS. Ferguson's complex surface. and Bezier surface used in CAD/CAM engineering based on. the results of this study.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.562-569
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• 2010

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the blurring of magnified image. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the blurring of magnified image. As a result, the nearest neighbor interpolation, which is the most frequently applied algorithm for the existing image interpolation algorithm, shows that the identification of a magnified image is not possible. Therefore, this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson' curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter, this study will develop an interpolation algorithm that has an excellent improvement for the boundary of the image and continuous and flexible property by using the NURBS, Ferguson' complex surface, and Bezier surface used in CAD/CAM engineering based on the results of this study.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2785-2788
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• 2001

In this paper, we present a new interpolation scheme for image enhancement using fuzzy inference. In general, interpolation techniques are based on linear operators which are essentially lowpass filters, hence, they tend to blur fine details in the original image. In our approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the properties of the input image data.

• Nuclear Engineering and Technology
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• v.31 no.3
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• pp.303-313
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• 1999

Various interpolation methods have been compared for reconstruction of LMR pin power distributions in hexagonal geometry. Interpolation functions are derived for several combinations of nodal quantities and various sets of basis functions, and tested against fine mesh calculations. The test results indicate that the interpolation functions based on the sixth degree polynomial are quite accurate, yielding maximum interpolation errors in power densities less than 0.5%, and maximum reconstruction errors less than 2% for driver assemblies and less than 4% for blanket assemblies. The main contribution to the total reconstruction error is made tv the nodal solution errors and the comer point flux errors. For the polynomial interpolations, the basis monomial set needs to be selected such that the highest powers of x and y are as close as possible. It is also found that polynomials higher than the seventh degree are not adequate because of the oscillatory behavior.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.656-659
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• 1996

An universal NURBS interpolation for an open architectured CNC controller is proposed in order to unify internal data structure and algorithm of different interpolations such as linear, circular and spline, and to intelligently interface CAD database of the various workpiece contour. Furthermore, NURBS interpolation may result in better surface roughness and high speed machining due to the continuous generation of cutter movement. The mathematical manipulation of NURBS is presented and the practical implementation on the CNC controller of a lathe is discussed for real machining. The comparison between a computer design and workpieces machined on a lathe shows the feasibility of the NURBS interpolation format as an universal interpolation scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.278-286
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• 2007

In this paper, an efficient algorithm is proposed for the interpolation of interlaced images. First of all, by efficiently estimating the directional spatial correlations of neighboring pixels, increased interpolation accuracy can be achieved. And then using the gradient vector which was obtained by Sobel operation, enables to consider the fine directional edges and make it possible to estimate the accurate direction of edges. In other words, it is possible to interpolate the interlaced images with considering the characteristics of images. In addition, by altering the conventional edge detector for the purpose of a easy De-interlacing and multiplying the optimal translation coefficients to each of the gradient vectors, an efficient interpolation for images can be achieved. Comparing with the conventional De-interlacing algorithms, proposed algorithm not only reduced the complexity but also estimated the accurate edge direction and the proposed scheme have been clearly verified that it enhances the objective and subjective image quality by the extensive simulations for various images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.1010-1019
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• 2010

This article presents a PDE-based interpolation algorithm to effectively reproduce high resolution imagery. Conventional PDE-based interpolation methods can produce sharp edges without checkerboard effects; however, they are not interpolators but approximators and tend to weaken fine structures. In order to overcome the drawback, a texture enhancement method is suggested as a post-process of PDE-based interpolation methods. The new method rectifies the image by simply incorporating the bilinear interpolation of the weakened texture components and therefore makes the resulting algorithm an interpolator. It has been numerically verified that the new algorithm, called the PDE-based image interpolator (PII), restores sharp edges and enhances texture components satisfactorily. PII outperforms the PDE-based skeleton-texture decomposition (STD) approach. Various numerical examples are shown to verify the claim.

• Transactions of Materials Processing
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• v.19 no.5
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• pp.320-324
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• 2010

Multi-Layer Ceramic Circuit(MLCC) in the face of thousands of fine pitch multi hole is processed. However, the fine pitch multi hole has a size of only a few micrometers. Therefore, in order to curtail the measurement time and reduce error, the image processing measurement method is required. So, we proposed an image processing measurement algorithm which is required to accurately measure the fine pitch multi hole. The proposed algorithm gets image of the fine pitch multi hole, extracts object from the image by morphological process, and extracts the parameters of its position and feature by edge detecting process. In addition, we have used the sub-pixel algorithm to improve accuracy. As a result, the proposed algorithm shows 97% test-retest measurement reliability within 2 ${\mu}m$. We found that the algorithm was wellsuited for measuring the fine pitch multi hole.

• Journal of IKEEE
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• v.3 no.2 s.5
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• pp.168-177
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• 1999

In this paper, we present a new interpolation scheme for image enhancement using fuzzy inference. In general, interpolation techniques are based on linear operators which are essentially lowpass filters, hence, they tend to blur fine details in the original image. In our approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the Properties of the input image data.