• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.828-833
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• 2005

Kernel methods have shown to improve the performance of conventional linear classification algorithms for complex distributed data sets, as mapping the data in input space into a higher dimensional feature space(7). In this paper, we propose a fuzzy kernel K-nearest neighbor(fuzzy kernel K-NN) algorithm, which applies the distance measure in feature space based on kernel functions to the fuzzy K-nearest neighbor(fuzzy K-NN) algorithm. In doing so, the proposed algorithm can enhance the Performance of the conventional algorithm, by choosing an appropriate kernel function. Results on several data sets and segmentation results for real images are given to show the validity of our proposed algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.11
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• pp.663-674
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• 2003

Bump mapping is a technique that represents the detailed parts of the object surface, such as a perturberance of the skin of a peanut, using the geometry mapping without complex modeling. However, the hardware implementation for bump mapping is considerable, because a large amount of per pixel computation, including the normal vector shading, is required. In this paper, we propose a new bump mapping algorithm using the polar coordinate system and its hardware architecture. Compared with other existing architectures, our approach performs bump mapping effectively by using a new vector rotation method for transformation into the reference space and minimizing illumination calculation. Consequently, our proposed architecture reduces a large amount of computation and hardware requirements.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.371-380
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• 2001

In this paper, lightness mapping for uniform color distribution and gamut mapping for maximum chroma reproduction are proposed. In the conventional lightness mapping, the average lightness difference between the two gamut is increased and different color changes in bright and dark regions are also increased. To solve these problems, a lightness mapping is proposed that minimizes the lightness difference of the cusps at each hue angle and produces same color changes in bright and dark regions. Also, gamut mapping that utilize variable anchor point and an anchor point are proposed for maximum chroma reproduction and uniform color change. Accordingly, the proposed algorithm can reproduce high quality images with low-cost color devices.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.634-646
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• 2015

Coarse-Grained Reconfigurable Architecture (CGRA) is a very promising platform that provides fast turn-around-time as well as very high energy efficiency for multimedia applications. One of the problems with CGRAs, however, is application mapping, which currently does not scale well with geometrically increasing numbers of cores. To mitigate the scalability problem, this paper discusses how to use the SIMD (Single Instruction Multiple Data) paradigm for CGRAs. While the idea of SIMD is not new, SIMD can complicate the mapping problem by adding an additional dimension of iteration mapping to the already complex problem of operation and data mapping, which are all interdependent, and can thus significantly affect performance through memory bank conflicts. In this paper, based on a new architecture called SIMD reconfigurable architecture, which allows SIMD execution at multiple levels of granularity, we present how to minimize bank conflicts considering all three related sub-problems, for various RA organizations. We also present data tiling and evaluate a conflict-free scheduling algorithm as a way to eliminate bank conflicts for a certain class of mapping problem.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.9-17
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• 2019

In this paper, we propose a block mapping technique applicable to NAND flash memory. In order to use the NAND flash memory with the operating system and the file system developed on the basis of the hard disk which is mainly used in the general PC field, it is necessary to use the system software known as the FTL (Flash Translation Layer). FTL overcomes the disadvantage of not being able to overwrite data by using the address mapping table and solves the additional features caused by the physical structure of NAND flash memory. In this paper, we propose a new mapping method based on the block mapping method for efficient use of the NAND flash memory. In the case of the proposed technique, the data modification operation is processed by using a blank page in the existing block without using an additional block for the data modification operation, thereby minimizing the block unit deletion operation in the merging operation. Also, the frequency of occurrence of the sequential write request and random write request Accordingly, by optimally adjusting the ratio of pages for recording data in a block and pages for recording data requested for modification, it is possible to optimize sequential writing and random writing by maximizing the utilization of pages in a block.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1666-1671
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• 2002

A lane sensing algorithm using vision sensors is developed based on lane geometry models. The parameters of the lane geometry models are estimated by a Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from image plane to global coordinate assumes earth to be flat, but roll and pitch motions of a vehicle are considered from the perspective of the lane sensing. The proposed algorithm shows robust lane sensing performance compared to the conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2365-2374
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• 1997

This paper describes two algorithms for technology mapping of multiple output functions into interesting and pupular FPGAs(Field Programmable Gate Array) that use look-yp table memories. For improvement of technology mapping for FPGA, we use the functional decompoition method for multiple output functions. Two algorithms are proposed. The one is the Roth-Karpalgorithm extended for multiple output functions. The other is the efficient algorithm which looks for common decomposition functions through the decomposition procedure. The cost function is used to minimize the number of CLBs and nets and to improve performance of the network. Finally we compare our new algorithm with previous logic design technique. Experimental resutls show sigificant reduction in the number of CLBs and nets.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.273-275
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• 2009

The currently used methods to get this information include corneal reflection, electro-oculograph, and so on. In this paper, we propose an algorithm that is developed for the reflection of pupil by infrared. I assume that the pupil is a perfect circle in the captured eye images. The method to recognize an existing image has many data throughput very much. And the time to deal with an image data is very long. So, we did not use the camera. However we studied the algorithm to pursue the pupil to a mapping technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.281-284
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• 2007

A realization for image distortion correction processing system with DSP processor is presented in this paper. The image distortion correcting algorithm is realized by DSP processor for focusing on more real time processing than image quality. The lens and camera distortion coefficients are processed by YCbCr Lookup Tables and the correcting algorithm is applied to reverse mapping method for geometrical transform. The system experimentation results in the processing time about 34.6 msec on $720{\times}480$ curved image at 150 degree visual range.

• East Asian mathematical journal
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• v.27 no.5
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• pp.545-555
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• 2011

Based on the A-maximal(m)-relaxed monotonicity frameworks, the approximation solvability of a general class of variational inclusion problems using the relaxed proximal point algorithm is explored, while generalizing most of the investigations, especially of Xu (2002) on strong convergence of modified version of the relaxed proximal point algorithm, Eckstein and Bertsekas (1992) on weak convergence using the relaxed proximal point algorithm to the context of the Douglas-Rachford splitting method, and Rockafellar (1976) on weak as well as strong convergence results on proximal point algorithms in real Hilbert space settings. Furthermore, the main result has been applied to the context of the H-maximal monotonicity frameworks for solving a general class of variational inclusion problems. It seems the obtained results can be used to generalize the Yosida approximation that, in turn, can be applied to first- order evolution inclusions, and can also be applied to Douglas-Rachford splitting methods for finding the zero of the sum of two A-maximal (m)-relaxed monotone mappings.