• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.12 s.354
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• pp.8-14
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• 2006

This paper proposed noise insensitive 4*4 mid frequency-OCT (MF-DCT) focus measure operator. Proposed operator enhanced low power 8*8 MDCT operator to have 4*4 rotationally same form for Gaussian noise. MF-DCT operator acting like band-pass filter suppresses both low-frequency signal useless for focus measure and high-frequency signal affected by impulsive noise. Also it is proved to be linear because it uses the energy of band-pass filtered signal as focus measure. Experimental result shows its superiority by comparing AUM with traditional operators.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1687-1693
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• 2015

Recently, demand for digital image processing devices increases rapidly, more clear images have been required. But, in the process of digital image acquisition, processing and transmission, image degradation occurs due to various external reasons and researches about noise reduction are on the rise. Therefore, this study suggested the algorithm to process AWGN(additive white Gaussian noise) by separately processing as three levels according to the pixel distribution in the mask in order to remove AWGN(additive white Gaussian noise) which is added in the image. Regarding the processed results by applying Barbara images which were damaged by AWGN(σ = 15), suggested algorithm showed the improvement by 2.87[dB], 2.95[dB], 2.88[dB], 1.52[dB], 1.49[dB], 1.58[dB] and 1.25[dB] respectively compared with the existing MF(5 × 5), A-TMF(5 × 5), AWMF(5 × 5), MF(3 × 3), A-TMF(3 × 3), AWMF(3 × 3), GF(5 × 5).

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.35.1-35.1
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• 2010

Unlike the initial mass function, the initial size distribution of globular cluster (GC) systems is not well known. We calculate the evolution of the mass function (MF), radial distribution (RD), and size distribution (SD) of the Galactic GC system. By comparing the results from this calculation and the present-day MF, RD, and SD of the Galactic GC system, we infer the initial SD of the GC system. We find that a Gaussian distribution of the half-mass radius and a Gaussian distribution of the half-mass to Jacobi radius ratio are the best-fit initial SDs of the Galactic GC system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.67-73
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• 2015

In a distribution of digital image, there is a serious problem that is the image alteration by a forger. For the problem solution, this paper proposes the forensic decision algorithm of a median filtering (MF) image using the feature vector based on a coefficient of variation (c.v.) of Fourier transform. In the proposed algorithm, we compute Fourier transform (FT) coefficients of row and column line respectively of an image first, then c.v. between neighboring lines is computed. Subsquently, 10 Dim. feature vector is defined for the MF detection. On the experiment of MF detection, the proposed scheme is compared to MFR (Median Filter Residual) and Rhee's MF detection schemes that have the same 10 Dim. feature vector both. As a result, the performance is excellent at Unaltered, JPEG (QF=90), Down scaling (0.9) and Up scaling (1.1) images, and it showed good performance at Gaussian filtering ($3{\times}3$) image. However, in the performance evaluation of all measured items of the proposed scheme, AUC (Area Under ROC (Receiver Operating Characteristic) Curve) by the sensitivity and 1-specificity approached to 1 thus, it is confirmed that the grade of the performance evaluation is rated as 'Excellent (A)'.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.118-120
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• 2021

In modern society, with the development of IoT technology, various digital equipment is being distributed in a wide range of fields such as CCTV and exploration robots. Accordingly, the importance of data processing is increasing, and various studies are being conducted to remove noise generated in the process of receiving data in the imaging field. Representative noise includes additive white Gaussian noise (AWGN), and existing filters for removing noise include an average filter (AF), an alpha trimmed average filter (A-TAF), and a median filter (MF). However, existing filters have a disadvantage in that they show somewhat insufficient performance in noise removal characteristics in high frequency areas. Therefore, in this paper, in order to effectively remove AWGN existing in the high frequency region, a weight filter according to a distance based on the standard deviation is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.415-419
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• 2008

Detecting and correcting defects on LCD glasses early in the manufacturing process becomes important for panel makers to reduce the manufacturing costs and to improve productivity. Many attempts have been made and were successfully applied to detect and identify simple defects such as scratches, dents, and foreign objects on glasses. However, it is still difficult to robustly detect low-contrast defect region, called Mura or blemish area on glasses. Typically, these defect areas are roughly defined as relatively large, several millimeters of diameter, and relatively dark and/or bright region of low Signal-to-Noise Ratio (SNR) against background of low-frequency signal. The aim of this article is to present a robust algorithm to segment these blemish defects. Early 90's, a highly robust estimator, known as the Model-Fitting (MF) estimator was developed by X. Zhuang et. al. and have been successfully used in many computer vision application. Compared to the conventional Least-Square (LS) estimator the MF estimator can successfully estimate model parameters from a dataset of contaminated Gaussian mixture. Such a noise model is defined as a regular white Gaussian noise model with probability $1-\varepsilon$ plus an outlier process with probability $varepsilon$. In the sense of robust estimation, the blemish defect in images can be considered as being a group of outliers in the process of estimating image background model parameters. The algorithm developed in this paper uses a modified MF estimator to robustly estimate the background model and as a by-product to segment the blemish defects, the outliers.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.79-84
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• 2015

In a distribution of digital image, there is a serious problem that is a distribution of the altered image by a forger. For the problem solution, this paper proposes a median filtering (MF) image forensic decision algorithm using a feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value' gradients of original image then 1th~6th order coefficients to be six feature vector. And the reconstructed image is produced by the solution of Poisson's equation with the gradients. From the difference image between original and its reconstructed image, four feature vector (Average value, Max. value and the coordinate i,j of Max. value) is extracted. Subsequently, Two kinds of the feature vector combined to 10 Dim. feature vector that is used in the learning of a SVM (Support Vector Machine) classification for MF (Median Filtering) detector of the altered image. On the proposed algorithm of the median filtering detection, compare to MFR (Median Filter Residual) scheme that had the same 10 Dim. feature vectors, the performance is excellent at Unaltered, Averaging filtering ($3{\times}3$) and JPEG (QF=90) images, and less at Gaussian filtering ($3{\times}3$) image. However, in the measured performances of all items, AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.661-663
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• 2016

Corruption occurs in the process of processing image signal and the corruption changes the pixel value within the image to damage the original information. AWGN(additive white Gaussian noise) is a representative example. For filters to remove AWGN, there are filters such as MF(mean filter), WF(wiener filter), and AWMF(adaptive weighted mean filter). However images processed through standard previous filters lock preservation characteristics in edge areas. Therefore, threshold value is applied for processing on the standard deviation of the local mask in this study and if the standard deviation is smaller than the threshold value, it is not filtered and if the value is bigger than the threshold value, the study suggested an algorithm that processes using weighted value utilizing standard deviation.

• Korean Journal of Optics and Photonics
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• v.11 no.5
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• pp.335-339
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• 2000

A $1.31/1.55\mu\textrm{m}$ coarse WDM opncal dIrectional coupler that conslsls of two idenlical straight channel waveguides in BK7 glass has been fabricated. The separatIOn between two channel waveguides is $8\mu\textrm{m}$ and the wavegu.ide width is $4\mu\textrm{m}$ . Especlally, we assumed that the index profile is Gaussian function and complementary error function in the width direction and depth direction, respectrvely. This directional coupler operating at $1.31/1.55\mu\textrm{m}$ with crosstalk of 18dB is demonstrated and has the 16 mm long length with 12.6 mm coupling region.region.