• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.6-11
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• 2012

Digital mammogram is effective for detecting the micro-calcification that is early symptom of breast cancer. In the digital mammogram, many image processing techniques have been studied for accurate diagnosis and efficient treatment of micro-calcification lesion. The wavelet based multi-scale method was mainly used to enhance the image contrast. This paper presents an advanced mammography enhancement method which is based both on the brightness and the contrast enhancement in the wavelet domain. The proposed method normalizes a dynamic range using histogram of the image. The brightness is enhanced by modifying coefficients of low frequency components, and the contrast is enhanced by coefficients of high frequency component based on the multi-scale contrast measure. The experiment results show that the proposed method yields better performance of the image enhancement over the existing methods.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.118-121
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• 2014

Image interpolation is a method of determining the value of new pixel coordinate in the process of image scaling. Recently, image contents are likely to be a large-capacity, interpolation algorithm is required to generate fast enhanced result image. In this paper, fast multiple mixed image interpolation for image resolution enhancement is proposed. The proposed method estimates expected 12 shortfalls from four sub-images of a input image, and generates the result image that is interpolated in the combination of the expected shortfalls with the input image. The experimental results demonstrate that PSNR increases maximum value of 1.9dB, SSIM increases maximum value of 0.052, and the subjective quality is superior to any other compared methods. Moreover, it is known by algorithm running time comparison that the proposed method has been at least three times faster than the compared conventional methods. The proposed method can be useful for application on image resolution enhancement.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.75-82
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• 2020

We identify the enhancement effects of zinc chloride and liquid nitrogen on low quality ninhydrin-developed fingerprint and we wanted to find out another cooling methods available for ninhydrin/Zn fingerprint enhancement besides the liquid nitrogen, which is hard to access. Artificial sweat was used to make the same level of fingerprints, and fingerprints developed by each technique were evaluated by SWGFAST standard and compared the average score and standard deviation. As a result of the experiment, ninhydrin/Zn-liquid nitrogen got 3.2 and 3.3 as average scores that enough to identify an individual such as 1,2-IND/Zn or DFO. Also, experiments using dry ice instead of liquid nitrogen as a way of the ninhydrin/Zn-developed fingerprints enhancement resulted in 3.0 and 2.9 as average scores, therefore, it was confirmed that dry ice is also a sufficient cooling method to be considered in practice in the field of forensic science.

• ETRI Journal
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• v.31 no.6
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• pp.741-748
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• 2009

We present an analysis of microstrip coupled lines (MCLs) used to improve the stability of a 60 GHz narrowband amplifier. The circuit has a 4-stage structure implementing MCLs instead of metal-insulator-metal (MIM) capacitors for the unconditional stability of the amplifier and yield enhancement. The stability parameter, U, is used to compare the stability of MCLs with that of MIM capacitors. Experimental results show that MCLs are more stable than MIM capacitors with the same capacitances as MCLs because the parasitic parallel resistances of MCLs are lower than those of MIM capacitors. Moreover, the bandwidth of an amplifier using MCLs is narrower than one using MIM capacitors because the parasitic series inductances of MCLs are higher than those of MIM capacitors.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.629-635
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• 1999

A second-order iterative learning control algorithm with feedback is proposed in this paper, in which a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is givenl, and the sufficient condition for the convergence of the algorithm is provided. And it also includes the discussions about the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial. Simulation results show the validity and efficiency of the proposed algorithm.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.231-234
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• 2009

Speckle noise reduction for power Doppler ventricle coherent image for restoration and enhancement using Fast Wavelet Transform with multi-thresholding and multi-filtering on the each subbands is presented. Fast Wavelet Transform divides into low frequency component image to high frequency component image to be multi-resolved. Speckle noise is located on high frequency component in multi-resolution image mainly. A Doppler ventricle image is transformed and inversed with separated threshold function and filtering from low to high resolved images for restoration to utilize visualization for ventricle diagnosis. The experimental result shows that the proposed method has better performance in comparison with the conventional method.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.185-193
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• 2022

There have been various studies in Korea to develop a %IMF(Intramuscular Fat Percentage) estimation method suitable for Hanwoo. Recently, a %IMF estimation method using a convolutional neural network (CNN), a kind of deep learning method among artificial intelligence methods, has been studied. In this study, we performed a performance comparison when various preprocessing methods were applied to the %IMF estimation of ultrasound images using CNN as mentioned above. The preprocessing methods used in this study are normalization, histogram equalization, edge enhancement, and a method combining normalization and edge enhancement. When estimating the %IMF of Hanwoo by the conventional method that did not apply preprocessing in the experiment, the accuracy was 98.2%. The other hand, we found that the accuracy improved to 99.5% when using preprocessing with histogram equalization alone or combined regularization and edge enhancement.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.81-87
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• 2022

In this paper, we propose a watershed algorithm that applies a high-frequency enhancement filter to emphasize the boundary and a local adaptive threshold to search for minimum points. The previous method causes the problem of over-segmentation, and over- segmentation appears around the boundary of the object, creating an inaccurate boundary of the region. The proposed method applies a high-frequency enhancement filter that emphasizes the high-frequency region while preserving the low-frequency region, and performs a minimum point search to consider local characteristics. When merging regions, a fixed threshold is applied. As a result of the experiment, the proposed method reduced the number of segmented regions by about 58% while preserving the boundaries of the regions compared to when high frequency emphasis filters were not used.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.77-80
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• 2001

This paper presents a new threshold-based denoising method by using undecimated discrete wavelet transform (UDWT). It proved excellency of the UDWT compared with orthogonal wavelet transform (OWT), spatia1ly selective noise filtration (SSNF) and NSSNF added new parameter. Methods using the spatial correlation are effectual at edge detection and image enhancement, whereas algorithm is complex and needs more computation However, UDWT is effective at denoising and needs less computation and simple algorithm.

• Convergence Security Journal
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• v.16 no.3_1
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• pp.87-98
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• 2016

As the informative society becomes intensified, the rise of the convergence security offers an alternative strategic correspondence to the technology leaks that are becoming more advanced, complex, and intelligent. In order to the convergence security to provide its efficacy, training convergence security specialists is essential. However, research on the subject has yet to be considered sufficient. Thus this research focuses on defense industry security specialists to define the duty and analze critical task as well as drawn and therefore the required academic level of the critical task was examined. These research work contributes to the competence development of convergence security specialists and further enhancement on convergence security training process of academic institutions and job training institutions.