• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.61-69
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• 2011

Dynamic Time Warping based on Dynamic Programming is the one of the most widely been used to compare the similarity of two patterns. DTW algorithm has two known problems. The one is singularities. And the another problem is the accuracy of the warping path with patterns. Therefore, this paper suggest the solution for DTW algorithm to use a 2nd derivative operator. Laplacian of Gaussian is a kind of a 2nd derivative operator. Consequently, our suggestion method to apply to this operator, more efficient to solve the singularities problems and to secure a accuracy of the warping path. And the result shows a superior ability of this suggested method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.19-26
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• 2005

In this paper, a new method for obtaining three-dimensional shape of an object by measuring relative blur between images using wavelet analysis has been described. Most of the previous methods use inverse filtering to determine the measure of defocus. These methods suffer from some fundamental problems like inaccuracies in finding the frequency domain representation, windowing effects, and border effects. Besides these deficiencies, a filter, such as Laplacian of Gaussian, that produces an aggregate estimate of defocus for an unknown texture, can not lead to accurate depth estimates because of the non-stationary nature of images. We propose a new depth from defocus (DFD) method using wavelet analysis that is capable of performing both the local analysis and the windowing technique with variable-sized regions for non-stationary images with complex textural properties. We show that normalized image ratio of wavelet power by Parseval's theorem is closely related to blur parameter and depth. Experimental results have been presented demonstrating that our DFD method is faster in speed and gives more precise shape estimates than previous DFD techniques for both synthetic and real scenes.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.601-608
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• 2014

In this study we propose an image denoising algorithm appropriate for mobile smart phone equipped with limited computing ability, which has better performance and at the same time comparable quality comparing with previous studies. The proposed image denoising algorithm for mobile smart phone cameras in low level light environment reduces computational complexity and also prevents edge smoothing by extracting just Gaussian noises from the noisy input image. According to the experiment result, we verified that our algorithm has much better PSNR value than methods applying mean filter or median filter. Also the result image from our algorithm has better clear quality since it preserves edges while smoothing input image. Moreover, the suggested algorithm reduces computational complexity about 52% compared to the method applying original Laplacian mask computation, and we verified that our algorithm has good denoising quality by implementing the algorithm in Android smart phone.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1342-1348
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• 2015

The objective of this study is to propose a method to calculate prediction intervals for one-day-ahead hourly forecasts of photovoltaic power generation and to evaluate its performance. One year of data of two systems, representing contrasting examples of forecast’ accuracy, were used. The method is based on the maximum likelihood estimation, the similarity between the input data of future and past forecasts of photovoltaic power, and on an assumption about the distribution of the error of the forecasts. Two assumptions for the forecast error distribution were evaluated, a Laplacian and a Gaussian distribution assumption. The results show that the proposed method models well the photovoltaic power forecast error when the Laplacian distribution is used. For both systems and intervals calculated with 4 confidence levels, the intervals contained the true photovoltaic power generation in the amount near to the expected one.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.24-29
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• 2014

Digital mammography is the most common technique for the early detection of breast cancer. To diagnose the breast cancer in early stages and treat efficiently, many image enhancement methods have been developed. This paper presents a multi-scale contrast enhancement method in the Laplacian pyramid for the digital mammogram. The proposed method decomposes the image into the contrast measures by the Gaussian and Laplacian pyramid, and the pyramid coefficients of decomposed multi-resolution image are defined as the frequency limited local contrast measures by the ratio of high frequency components and low frequency components. The decomposed pyramid coefficients are modified by the contrast measure for enhancing the contrast, and the final enhanced image is obtained by the composition process of the pyramid using the modified coefficients. The proposed method is compared with other existing methods, and demonstrated to have quantitatively good performance in the contrast measure algorithm.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.450-461
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• 2005

In this paper, we derive analytical expressions for the exact pairwise error probability (PEP) of a space-time coded system operating over spatially correlated fast (constant over the duration of a symbol) and slow (constant over the length of a code word) fad­ing channels using a moment-generating function-based approach. We discuss two analytical techniques that can be used to evaluate the exact-PEPs (and therefore, approximate the average bit error probability (BEP)) in closed form. These analytical expressions are more realistic than previously published PEP expressions as they fully account for antenna spacing, antenna geometries (uniform linear array, uniform grid array, uniform circular array, etc.) and scattering models (uniform, Gaussian, Laplacian, Von-mises, etc.). Inclusion of spatial information in these expressions provides valuable insights into the physical factors determining the performance of a space-time code. Using these new PEP expressions, we investigate the effect of antenna spacing, antenna geometries and azimuth power distribution parameters (angle of arrival/departure and angular spread) on the performance of a four-state QPSK space-time trellis code proposed by Tarokh et al. for two transmit antennas.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.321-325
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• 2004

Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. It can be characterized by inappropriate and disorganized vessel. This paper present a method for blood vessel detection on infant retinal images. The algorithm is designed to detect the retinal vessels. The proposed method applies a Lapalacian of Gaussian as a step-edge detector based on the second-order directional derivative to identify locations of the edge of vessels with zero crossings. The procedure allows parameters computation in a fixed number of operations independent of kernel size. This method is composed of four steps : grayscale conversion, edge detection based on LOG, noise removal by adaptive Wiener filter & median filter, and Otsu's global thresholding. The algorithm has been tested on twenty infant retinal images. In cooperation with the Digital Imaging Research Centre, Kingston University, London and Department of Opthalmology, Imperial College London who supplied all the images used in this project. The algorithm has done well to detect small thin vessels, which are of interest in clinical practice.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.151-156
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• 2012

In this paper robust nonlinear image denoising algorithms are introduced for the distribution which is Gaussian in the center and Laplacian in the tails. The distribution is known as the least favorable ${\epsilon}$-contaminated normal distribution that maximizes the asymptotic variance. The proposed filter proves to be the maximum likelihood estimator under the heavy-tailed Gaussian noise environments. It is optimal in the respect of maximizing the efficacy under the above noise environment. Another filter for reducing impulsive noise is proposed by mixing with the myriad filter to propose an amplitude-limited myriad filter. Extensive experiment is conducted with images corrupted with ${\alpha}$-stable noise to analyze the behavior and performance of the proposed filters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.136-138
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• 2022

Edge detection includes information such as the shape, position, size, and material of an object with respect to an image, and is a very important factor in analyzing the characteristics of the image. Existing edge detection methods include Sobel edge detection filter, Roberts edge detection filter, Prewitt edge detection filter, and LoG (Lapacian of Gaussian) using secondary differentials. However, these methods have a disadvantage in that the edge detection results are somewhat insufficient because a fixed weight mask is applied to the entire image area. Therefore, in this paper, we propose an edge detection algorithm that increases edge detection characteristics by considering the center pixel in the mask. In addition, in order to confirm the proposed edge detection performance, it was compared through simulation result images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1685-1692
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• 2010

The Laplacian operator is usually used as a regularization operator which may be used as any differential operator in the regularization iterative processing. In this paper, several kinds of differential operator and proposed operator as a regularization operator were compared with each other performance. For noisy gaussian-blurred images, proposed operator worked better in the edge, while in flat region the conventional operator resulted better. In regularization, smoothing the noise and restoring the edges should be considered at the same time, so the regions divided into the flat, the middle, and the detailed, which were processed in separate and compared.