• Journal of ILASS-Korea
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• v.15 no.2
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• pp.53-60
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• 2010

This study presents development of digital particle holographic system and its application to spray field to measure three-dimensional velocities and sizes of spray droplets. A double exposure hologram recording system with synchronization system for time control was established and digital holograms can be recorded in a short time interval. To process recorded holograms, the correlation coefficient method was used for focal plane determination of particles. To remove noises and improve the quality of holograms and reconstructed images, the Wiener filter was adopted. The two-threshold and image segmentation methods were used in binary image transformation. For particle pairing, the match probability method was adopted. The developed system was applied to spray field and three-dimensional velocities and sizes of spray droplets were measured. The measurement results of digital holographic system were compared with those made by laser instruments, PDPA(Phase Doppler Particle Analyzer), which proved the feasibility of in-line digital particle holographic system as a good measurement tool for spray droplets.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.5
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• pp.28-35
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• 2015

This paper introduces a resistance scanning-type flexible tactile sensor for intelligent robots and presents the output characteristics of the sensor via signal processing. The sensor was produced via the lamination method using multi-walled carbon nanotubes (a conductive material), an insulator, and Tango-plus (an elastic material). Analog and digital signal processing boards were produced to analyze the output signal of the sensor. The analog signal processing board was made up of an integrator and an amplifier for signal stability, and the digital signal processing board was made up of an IIR filter for noise removal. Finally, the sensor output for the contact force was confirmed through experiments.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.45-55
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• 2000

In this paper, we proposed the hardware architecture of wavelet transform digital filter for an image processing. Filter bank pyramid algorithm is used for wavelet transform and each fillet is implemented by the FIR filter. For DWT computation, because the memory controller is implemented by hardware, we can efficiently process the multisolution decomposition of the image data only input the parameter. As a result of the image Processing in this paper, 33㏈ PSNR has been obtained on 512$\times$512 B/W image due to 11-bit mantissa processing in FPGA Implementation. And because of using QMF( Quadrature Mirror Filter) properties, it reduces half number of the multiplier needed DWT(Discrete Wavelet Transform) computation so the hardware size is reduced largely. The proposed scheme can increase the efficiency of an image Processing as well as hardware size reduced. The hardware design proposed of DWT fillet bank is synthesized by VHDL coding and then the test board is manufactured, the operating Program and the application Program are implemented using MFC++ and C++ language each other.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.903-905
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• 2015

The need for digital devices is increasing in the digital age. In general, noise in images occurs during the process of compression, recognition and processing due to many reasons. Some of the filters used to remove salt and pepper noise include SMF, CWMF and AMF. In areas where the noise density is high, the removal of noise is undermined. This paper suggests an adjusted median filter algorithm that preserves the non-noise pixels while transforming the noise pixels to more effectively remove salt and pepper noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2265-2271
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• 2014

In modern society digital equipments that are related with various hardware and software are popularized, and digital images are widely applied in the field of production and scientific research. In general, however, images are degraded by the noise in the process of transmission and storage. In this paper, to reduce the influence of mixed noises, the algorithm in which noises in the space area are classified into impulse noise and Gaussian noise and this is processed by applying weighted value, while that is processed by modified nonlinear filter is proposed. And the excellence of the proposed algorithm is judged by PSNR(peak signal to noise ratio).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.404-406
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• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• Transactions on Electrical and Electronic Materials
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• v.15 no.4
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• pp.230-234
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• 2014

Automatic detection of disease helps medical institutions that are introducing digital images to read images rapidly and accurately, and is thus applicable to lesion diagnosis and treatment. The aim of this study was to apply a symmetry contribution algorithm to unsharp mask filter-applied MR images and propose an analysis technique to automatically recognize brain tumor and edema. We extracted the skull region and drawed outline of the skull in database of images obtained at P University Hospital and detected an axis of symmetry with cerebral characteristics. A symmetry contribution algorithm was then applied to the images around the axis of symmetry to observe intensity changes in pixels and detect disease areas. When we did not use the unsharp mask filter, a brain tumor was detected in 60 of a total of 95 MR images. The disease detection rate for the brain was 63.16%. However, when we used the unsharp mask filter, the tumor was detected in 87 of a total of 95 MR images, with a disease detection rate of 91.58%. When the unsharp mask filter was used in the pre-process stage, the disease detection rate for the brain was higher than when it was not used. We confirmed that unsharp mask filter can be used to rapidly and accurately to read many MR images stored in a database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2329-2338
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• 1997

A conventional digital receiver sampled a baseband signal and processed it digitally for demodulation. But now we can sample at sufficiently high speed a wideband signal to take enough discrete data values due to the advent of economic high-speed ADC. With this technical background, a wideband frequency-division-multiplexed signal can be undersampled and channelized in digital domain by DFT analysis filter using the theory of polyphase. In this paper, we propose a new digital receiver which can digitally process the multichannel received signal by sampling at IF band, develop a mathematical theory and algorithm, and analyze the performance by using C-language simulaation. The proposed receiver can demodulate analog and digital FM signals.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.12-18
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• 2020

In semiconductor manufacturing, defect detection is critical to maintain high yield. Currently, computer vision systems used in semiconductor photo lithography still have adopt to digital image processing algorithm, which often occur inspection faults due to sensitivity to external environment. Thus, we intend to handle this problem by means of using Mask R-CNN instead of digital image processing algorithm. Additionally, Mask R-CNN can be trained with image dataset pre-processed by means of the specific designed digital image filter to extract the enhanced feature map of Convolutional Neural Network (CNN). Our approach converged advantage of digital image processing and instance segmentation with deep learning yields more efficient semiconductor photo lithography inspection system than conventional system.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.49-59
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• 2012

Throughout developing digital technology, reproduction of image is growing better day by day. And at the same time, diverse image editing softwares are developed to manage images easily. In the process of editing images, those programs could delete or modify EXIF files which have the original image information; therefore images without the origin source are widely spread on the web site after editing. This matter could affect analysis of images due to the distortion of originality. Especially in the court of law, the source of evidence should be expressed clearly; therefore digital image EXIF file without deletion or distortion could not be the objective evidence. In this research, we try to trace the identification of a digital camera in order to solve digital images originality, and also we focus on lens distortion correction algorism which is used in digital image processing. Lens distortion correction uses mapping algorism, and at this moment it also uses interpolation algorism to prevent aliasing artifact and reconstruction artifact. At this point interpolation shows the similar mapping pattern; therefore we want to find out the interpolation evidence. We propose a minimum filter algorism in order to detect interpolation pattern and adjust the same minimum filter coefficient in two areas; one has interpolation and the second has no interpolation. Throughout DFT, we confirm frequency character between each area. Based on this result, we make the final detection map by using differences between two areas. In other words, thereby the area which has the interpolation caused by mapping is adjusted using minimum filter for detection algorism; the second area which has no interpolation tends to different frequency character.