• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.482-485
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• 2000

A modified watershed transform is proposed which is context-free marker-controlled and minima imposition-free to reduce the over-segmentation and to speedup the transform. In contrast to the conventional methods in which a priori knowledge, such as flat zones, zones of homogeneous texture, and morphological distance, is required for marker extraction, context-free marker extraction is proposed by using the attention operator based on the GST (generalized symmetry transform). By using the context-free marker, the proposed watershed transform exploit marker-constrained labeling to speedup the computation and to reduce the over-segmentation by eliminating the unnecessary geodesic reconstruction such as the minima imposition and thereby eliminating the necessity of the post-processing of region merging. The simulation results show that the proposed method can extract context-free markers inside the objects from the complex background that includes multiple objects and efficiently reduces over-segmentation and computation time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.762-763
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• 2016

In realizing a homomorphic encryption system, the operations of encrypt, decypt, and recrypt constitute major portions. The most important common operation for each back-bone operations include a polynomial modulo multiplication for over million-bit integers, which can be obtained by performing integer Fourier transform, also known as number theoretic transform. In this paper, we adopt and modify an algorithm for calculating big integer multiplications introduced by Schonhage-Strassen to propose an efficient algorithm which can save memory. The proposed architecture of number theoretic transform has been implemented on an FPGA and evaluated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1624-1632
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• 1996

Wavelet transform is widely used for high compression ratio image compression. It requeires a large memory when it is implemented by a hardware. Therefore, it is efficient to divide the entire image into blocks. Because the wavelet transform for divided blocks causes losses, pixels of the adjacent blocks are used. In the case of color image compression, the image is decomposed into brightness and color components, and then color components are downsampled. When the wavelet transform is performed by using pixels of adjacentblocks, the number of necessary pixels are doubled due to downsampling of color components. In this paper, we propose an efficient block wavelet transform using variablefilter length for brightness and color components. By using the proposed method, the number of pixels of adjacent blocks is optimized. We show the degradation of image quality due to the reduction of filter length for color components is negligible through simulations.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.169-172
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• 1999

Recently, the wavelet transform has been a new and powerful tool for signal processing. It is more suitable specially for the feature extraction and detection of non-stationary signals than traditional methods such as, the Fourier Transform(FT), the Fast Fourier Transform(FFT) and the Least Square Method etc. because of the characteristic of the multi-scale analysis and time-frequency domain localization. The wavelet transform has been developed for the analysis of PD pulse signal to raise in the progress of insulation degradation. In this paper, the wavelet transform was applied to one foundational method for feature extraction. For the obtain experimental data, a computer-aided partial discharge measurement system with a single acoustic sensor was used. If we are applying to the neural network method the accumulated data through the extracted feature, it is expected that we can detect the PD pulse signal in the insulation materials on the on-line.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.51-56
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• 2018

This paper proposes the efficient preprocessing method based on curvelet transform for edge enhancement in image. The propose method is generated the edge map by using the Canny algorithm to wavelet transform, which is the sub-step of the curvelet transform. In order to improve the part of edge feature, the selective sharpening according to the generate edge map is applied. In experimental result, the propose method achieves that the enhancement of edge feature is better than conventional methods. This leads that peak to signal noise ratio, edge intensity are improvement on average about 1.92, 1.12dB respectively.

• Korean Journal of Optics and Photonics
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• v.8 no.3
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• pp.199-203
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• 1997

Fine displacement of spherical suface was detected and analyzed by Twyman-Green interferometer and the interferogram analysis using Fourier transform method. The surface profile was obtained from single interferogram by introducing the carrier freguency to the interferogram. The interferogram was processed in the spatial frequency domain by fast Fourier transform, and the phase distribution was obtained by inverse Fourier transform. The 3-dimensional distribution for the surface displacement was obtained. It was compared with the calculated surface displacement and the error was less than λ/10.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.571-579
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• 1999

In this paper, a Hadamard transform imaging spectrometer(HTIS) is proposed by using a grill spectrometer. And we reconfigure the system by using the grill sectrometer which uses a left cyclic S-matrix instead of the conventional right cyclic one. Then, we model the Hadamard transform imaging spectrometer and apply the mask characteristics compensation method, i.e. $ {T}^{-1}$ method, to complete fast algorithm. Also, through computer simulations the superiority of the proposed system in this paper to the conventional Hadamard transform spectrometer(HTS) is proved and the performance of the two systems are compared by introducing average mean square error(AMSE) as the algebraic criterion.

• Journal of Biomedical Engineering Research
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• v.15 no.1
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• pp.83-88
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• 1994

The transform trellis code is an optimal source code as a block size and the constraint length of a shift register go to infinite for stationary Gaussian sources with the squared-error distortion measure. However to implement this code, we have to choose the finite block size and constraint length. Moreover real-world sources are inherently non stationary. To overcome these difficulties, we developed a training algorithm for the transform trellis code. The trained transform trellis code which uses the same rates to each block led to a variation in the resulting distortion from one block to another. To alleviate this non-uniformity in the encoded image, we constructed clusters from the variance of the training data and assigned different rates for each cluster.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.3
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• pp.105-111
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• 2001

The research presented in this paper focuses on a method for the detection of High Impedance Fault(HIF). The method will use the wavelet transform and neural network system. HIF on the multi-grounded three-phase four-wires primary distribution power system cannot be detected effectively by existing over current sensing devices. These paper describes the application of discrete wavelet transform to the various HIF data. These data were measured in actual 22-9kV distribution system. Wavelet transform analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate HIF from the normal status by a gradient descent method. The proposed method performed very well by proving the right state when it was applied staged fault data and normal load mimics HIF, such as arc-welder.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.665-668
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• 2002

본 논문은 카메라를 수평이동시켜 얻어진 영상을 Mellin Transform을 이용하여 파노라마 이미지를 구성하는 방법을 제안한다. 일반적으로 카메라로부터 얻어진 동영상은 각 프레임 사이에 많은 시간적, 공간적 정보가 중복되어 있다. 이러한 중복 정보는 모자이크 방법 중의 하나인 파노라믹 기법을 사용하여 줄일 수 있다. 지금까지의 제안된 이미지의 중복성을 찾는 알고리즘들은 노이즈에 지나치게 민감하거나 중복성을 계산하는 데 있어 시간이 많이 소모되는 단점이 있었다. 따라서 본 논문에서는 Mellin Transform 을 사용하여 노이즈에 덜 민감하고 빠른 시간에 이미지의 중복 정보를 찾아내는 방법을 제안한다. Mellin Transform을 이용하여 생성된 파노라마 영상은 이미지의 이동정보를 쉽게 구할 있어 동영상에서 움직이는 물체를 추적하거나 추정이 가능하여 물체 tracking 영역에 응용될 수 있을 것으로 보이며 또한 앞으로 현실감 있는 가상현실의 배경 생성에 도움이 될 것으로 생각된다.