• Journal of the Korea Society for Simulation
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• v.9 no.4
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• pp.11-23
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• 2000

The purpose of format conversion is to convert a wide range of personal computer video formats into a target format. Circuits for the conversion have been developed by means of interpolation techniques, such as zero-order interpolation, bilinear interpolation, and bisigmoidal interpolation. This paper proposes a scan converter using cubic splines. The converter was modeled in VHDL, simulated on Max+plus Ⅱ , and implemented with an FPGA chip. The circuit gives much better conversion performance than a scan converter with zero-order or linear interpolation techniques according to simulation results and implementation.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.04a
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• pp.91-95
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• 2000

The purpose of format conversion is to convert a wide range of personal computer video formats to a target format. Circuits for the conversion has been developed by means of interpolation techniques, such as zero-order interpolation, bilinear interpolation, and bisigmoidal interpolation. This paper proposes a scan converter using cubic splines. The converter was modeled in VHDL on Max+Plus II and implemented with an FPGA cpip. The circuit gives much better conversion performance than a scan converter with zero-order or linear interpolation.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3165-3168
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• 1999

When a input image is extensively magnified on the computer system, it is almost impossible to replicate the original shape because of mismatched coordinates system. In order to resolve the problem, the shape of the magnified image has been reconfigured using the bilinear interpolation method, low pass special filtering interpolation method and B-spline interpolation method. Ferguson curve interpolation method based on the CAD/CAM curve interpolation algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.376-379
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• 1995

To force an aircraft to track the specified path, the generation of the smooth desired trajectory is essential. In this paper, the cubic spline function is used to generate the trajectory which passes through the specified intercept points. The simulation results show that the desired trajectory generated by the spline interpolation is very smooth and the aircraft tracks it with small position errors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.691-693
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• 2017

As the modern society develops into the digital information age, the application field is gradually expanded and used as an important field. The image data is deteriorated due to various causes in the process of transmitting the image, and typically there is salt & pepper noise. Conventional methods for removing salt & pepper noise are somewhat lacking in noise canceling characteristics. In this paper, we propose a weighted filter using the histogram of the image damaged by salt & pepper noise and a spline interpolation method according to the direction of the local mask.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.479-491
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• 2004

Location information of mobile objects is applied to vehicle tracking, digital battlefields, location based services, and telematics. Their location coordinates are periodically measured and stored in the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the mobile object moving on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function, although the proposed location estimation function uses the small amount of information. The proposed method has an advantage that drops the cost of data storage space and communication for the management of location information of the mobile objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.685-690
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• 2008

In numerically evaluating the thermal performance of the heat exchanger, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be directly used without modelling. In this study the applicability of neural networks in modelling superheated water vapor was examined. The multi-layer neural networks consist of an input layer with 2 nodes, two hidden layers with 15 and 25 nodes respectively and an output layer with 3 nodes. Quadratic spline interpolation was also applied for comparison. Neural networks model revealed smaller percentage error compared with spline interpolation. From this result, it is confirmed that the neural networks could be a powerful method in modelling the superheated water vapor.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.65-85
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• 1999

Objectives: To determine the effect of interpolation functions when processing the digital periapical images. Material and Methods: The digital images were obtained by Digora and CDR system on the dry skull and human subject. 3 oral radiologists evaluated the 3 portions of each processed image using 7 interpolation methods, and ROC curves were obtained by trapezoidal methods. Results: The heighest Az value(0.96) was obtained with cubic spline method and the lowest Az value(0.03) was obtained with facet model method in Digora system. The heighest Az value (0.79) was obtained with gray segment expansion method and the lowest Az value(0.07) was obtained with facet model method in CDR system. There was significant difference of Az value in original image between Digora and CDR system at a=0.05 level. There were significant differences of Az values between Digora and CDR images with cubic spline method, facet model method, linear interpolation method and non-linear interpolation method at α=0.1 level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.681-683
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• 2017

In the digital information age, image processing is essential for various digital devices such as smart phones, cameras, and TVs. However, degradation occurs in analyzing, recognizing, and processing image data, and salt & pepper noise occurs. Therefore, in this paper, we applied linear interpolation method, newton interpolation method, lagrange interpolation method, and spline interpolation method to the image damaged by salt & pepper noise in order to find more effective interpolation method in salt & pepper noise environment, The methods were compared using the PSNR (peak signal to noise ratio).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.413-418
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• 2011

The thermodynamic properties of steam table are obtained by measurement or approximate calculation under appropriate assumptions. Therefore they are supposed to have basic measurement errors. And thermodynamic properties should be modeled through function approximation for using in numerical analysis. In order to make noised thermodynamic properties corresponding to measurement errors, random numbers are generated, adjusted to appropriate magnitudes and added to original thermodynamic properties. Both neural networks and quadratic spline interpolation method are introduced for function approximation of these modified thermodynamic properties in the saturated water based on pressure and temperature. In analysis spline interpolation method gives much less relative errors than neural networks at both ends of data. Excluding the both ends of data, the relative errors of neural networks is generally within ${\pm}0.2%$ and those of spline interpolation method within ${\pm}0.5$~1.5%. This means that the neural networks give smaller relative errors compared with quadratic spline interpolation method within range of use. From this fact it was confirmed that the neural networks trace the original values better than the quadratic interpolation method and neural networks are more appropriate method in modelling the saturated steam table.