• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.75-82
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• 1998

Conventional vector quantization (VQ) codebook design methods have several drawbacks such as edge degradation and high computational complexity. In this paper, we first made activity coordinates from the horizonatal and the vertical activity of the input block. Then it is mapped on the 2-dimensional interconnected codebook, and the codebook is designed using kohonen self-organizing map (KSFM) learning algorithm after the search of a codevector that has the minumum distance from the input vector in a small window, centered by the mapped point. As the serch area is restricted within the window, the computational amount is reduced compared with usual VQ. From the resutls of computer simulation, proposed method shows a better perfomance, in the view point of edge reconstruction and PSNR, than previous codebook training methods. And we also obtained a higher PSNR than that of classified vector quantization (CVQ).

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.651-659
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• 2005

For segmentation of constrained and handwritten Hangul, a new method, which has been not introduced, was proposed and implemented to use virtual network search system in the space between characters. The proposed system was designed to be used in all cases in unconstrained handwritten Hangul by various writers and to make a number of curved segmentation path using a virtual network to the space between characters. The proposed system prevented Process from generating a path in a wrong position by changing search window upon target block within a search process. From the experimental results, the proposed virtual network search system showed segmentation accuracy of $91.4\%$ from 800 word set including touched and overlapped characters collected from various writers.