• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.519-521
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• 2015

세라믹 소재 영상에서 결함 영역이 다른 영역보다 명암도가 밝게 나타나는 정보를 이용하여 ROI 영역을 추출한다. 추출된 ROI 영역에서 Blurring 기법을 적용하여 미세 잡음을 제거한다. 미세 잡음이 제거된 ROI 영역에서 Median Filter기법을 적용하여 임펄스 잡음을 제거한다. 임펄스 잡음이 제거된 영역에서 Prewit Mask을 적용하여 수평과 수직 에지를 검출하고 검출된 에지에 윤곽선 추적 기법을 적용하여 결함 영역의 경계를 보정한다. 보정된 영상에서 Blob Labeling 기법을 적용하여 최종적으로 결함 영역을 추출한다. 제안된 방법을 8mm와 10mm 세라믹 소재 영상을 대상으로 실험한 결과, 기존의 결함 검출 방법보다 제안된 검출 방법의 검출 성능이 개선된 것을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2343-2348
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• 2006

Image magnification is among the basic image processing operations. The most commonly used technique for image magnification are based on interpolation method(such as nearest neighbor, bilinear and cubic interpolation). However, the magnified images produced by the techniques that often appear a variety of undesirable image artifacts such as 'blocking' and 'blurring' or too takes the processing time into the several processing for image magnification. In this paper, we propose image magnification method which uses input image's sub-band information such as edge information to enhance the image magnification method. We use the whole image and not use the one's neighborhood pixels to detect the edge information of the image that isn't occurred the blocking phenomenon. And then we emphasized edge information to remove the blurring phenomenon which incited of edge information. Our method, which improves the performance of the traditional image magnification methods in the processing time, is presented. Experiment results show that the proposed method solves the drawbacks of the image magnification such as blocking and blurring phenomenon, and has a higher PSNR and Correlation than the traditional methods.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.542-553
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• 2005

Recommendation systems analyze user preferences and recommend items to a user by predicting the user's preference for those items. Among various kinds of recommendation methods, collaborative filtering(CF) has been widely used and successfully applied to practical applications. However, collaborative filtering has two inherent problems: data sparseness and the cold-start problems. If there are few known preferences for a user, it is difficult to find many similar users, and therefore the performance of recommendation is degraded. This problem is more serious when a new user is first using the system. In this paper we propose a method of integrating additional feature information of users and items into CF to overcome the difficulties caused by sparseness and improve the accuracy of recommendation. In our method, we first fill in unknown preference values by using the probability distribution of feature values, then generate the top-N recommendations by applying collaborative filtering on the modified data. We call this method of filling unknown preference values as data blurring. Several experimental results that show the effectiveness of the proposed method are also presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.825-828
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• 2006

The most commonly used techniques for image magnification are interpolation based. However, the magnified images produced by this technique often appear blocking and blurring phenomenon when the image is enlarged. In this paper, we enhanced image magnification algorithm using edge information. The proposed algorithm not used interpolation based but by using sub-band of input image in extrapolation. According to mapping relationship in pyramid, we calculated up-band information to magnify. In experiments, the proposed model shows solved the problem of image loss like the blocking and blurring phenomenon. As the result, it is faster and higher resolution than traditional magnification algorithms.

• Korean Journal of Digital Imaging in Medicine
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• v.15 no.2
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• pp.55-61
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• 2013

The purpose of this study is to evaluate image blurring according to variation of the ETL and propose the clinically appropriate ETL range. SIEMENS MAGNETOM Skyra 3.0T and 20 channel head coil were used for the study. MRI phantom was kept the lines horizontally to three direction(X,Y,Z) of the coil and T1, T2 weighted images that used the fast spin echo technique acquired. The ETL with increase of 10 was applied from 10 to 80. In addition, the ETL with increase of 1 was applied in the interval statistically significant differences occurred. And T1, T2 weighted images that used the conventional spin echo technique acquired to compare image blurring of the images that used the fast spin echo technique. The slope of lattice in the images was measured using Image J 1.47v program to evaluate image blurring. And image blurring was determined by the degree of the slope. The statistical significance of both techniques was evaluated by the Kruskal-Wallis test of the SPSS 17.0v. And the correlation of the ETL and image blurring was evaluated quantitatively by regression analysis. The slope of the T1, T2 weighted images that used fast spin echo technique decreased as contrasted with conventional spin echo technique. In the result of the Kruskal-Wallis test, the T1, T2 weighted images that used fast spin echo technique made a significant difference with conventional spin echo technique. Particularly, in the Tomhane' T2 test, the T1, T2 weighted images made a significant difference from ETL 22 and 31 respectively. In the result of the regression analysis, the R-squared of the T1, T2 weighted images are 0.762 and 0.793. It is difficult to apply the long ETL in the T1 weighted image caused by the short TR and multi-slices study. Therefore, clinical impact according to variation of the ETL is very slight in the T1 weighted images. But the application of the proper ETL is demanded in T2 weighted images using the fast spin echo technique in order to prevent image blurring.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.2
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• pp.176-188
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• 1987

This paper presents a method for Digital Image Motion Restoration by inverse filtering. In order to onstruct optimal Restoration filter, We exactly have to model the degradation process, and therefrom, derive the inverse filter which has inverse charateristics of the degradation model. An Image taken from object which moves fast, is o suffer blurring. it can be modeled by integration process mathematically and analyzed to convolve a rectangular window over an image. in this paper, We analyzed it in the frequency domain, and studied a method for motion restoration using inverse filter has a directional Sinc property.

• Korean Journal of Remote Sensing
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• v.26 no.4
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• pp.395-401
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• 2010

Image enhancement algorithm aims to improve the visual quality of low contrast image through eliminating the noise and blurring, increasing contrast, and raising detail. This paper proposes adaptive dynamic range linear stretching(ADRLS) algorithm based on advantages of existing methods. ADRLS method is focused on generating sub-histograms of the majority through partitioning the histogram of input image and applying adaptive scale factor. Generated sub-histograms are finally applied by linear stretching(LS) algorithm. In order to validate proposed method, it is compared with LS and histogram equalization(HE) algorithm generally used. As the result, the proposed method show to improve contrast of input image and to preserve distinct characteristics of histogram by controlling excessive change of brightness.

• Convergence Security Journal
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• v.22 no.4
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• pp.141-146
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• 2022

The iris, a biometric information, is safe, unique, and reliable, such as fingerprints, and is personal information that can significantly lower the misrecognition rate than other biometric authentication. However, due to the nature of biometric authentication, it is impossible to replace it if it is stolen. There is a case in which an actual iris photo is taken and 3d printed so that the eyes work as if they were in front of the camera. As such, there is a possibility of iris leakage through high-definition images and photos. In this paper, we propose to improve iris masking performance by supplementing iris region masking research based on existing blurring techniques. Based on the results derived in this study, it is expected that it can be used for the security of video conference programs and electronic devices.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.9-20
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• 2000

In this paper we compare two frequency domain digital watermarking methods for digital Images, namely DCT(Discrete Cosine Transform) based and DFT(Discrete Fourier Transform) based methods. Unlike DCT coefficients, which always have real values, DFT coefficients normally have complex values Therefore, the DFT coefficients have amplitude and phase components Among them, the phase components are known to carry more Important information for the Images. So, we insert the watermark to the phase of the DFT coefficients only This DFT watermarking method is compared with the conventional DCT based watermarking method for the object-based watermarking problem. Experimental results show that the DFT-phase based method IS more robust to general Image processing attacks including resize, lossy compression(JPEG), blurring and median filtering. On the other hand, the DCT based method is more robust to the malicious attack which inserts different watermarks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.245-249
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• 2007

In this paper describes image enhancement technique using deconvolution processing for ultrasonic nondestructive testing. When flaws are detected fur B-scan or C-scan, blurring effect which is caused by the moving intervals of transducer degrades the quality of images. In addition, acquisited images suffer form speckle noise which is caused by the ultrasonic components reflected from the grain boundary of material (1,2). The deconvolution technique can restore sharp peak value or clean image from blurring signal or image. This processing is applied to C-scan image obtained from known specimen. Experimental results show that the deconvolution processing contributes to get improved the quality of C-scan images.