• KSCI Review
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• v.14 no.2
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• pp.141-146
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• 2006

In this paper, we propose a new algorithm for recovering the broken letters of relics into an original form by using Z-map and image processing. The letters of relics may have been broken by a lot of rubbed copy and a long time and tide. They need to be restored. But the manual reconstruction is a very tedious and laborious task. Thus, it is necessary to automate the restoration process. This paper presents a realistic algorithm with an application to Tripitaka Koreana by using Z-map and morphological filter.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.147-152
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• 2005

This paper proposes an evaluates a new approach to detect ships as targets from Radarsat-1 SAR (Synthetic Aperture Radar) imagery in the vicinity of Korean peninsula. To be more specific, a labeling technique and morphological filtering in conjunction with some other methods are employed to automatically detect the ships. From the test, the ships are revealed to be detected. For ground truth data, information from a radar system is used, which allows assessing accuracy of the approach. The results showed that the proposed approach has the high potential in automatically detecting the ships.

• KSTLE International Journal
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• v.3 no.1
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• pp.54-59
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• 2002

It can be effective on failure diagnosis of oil-lubricated tribological system to analyze operating conditions with morphological characteristics of wear debris in a lubricated machine. And it can be recognized that results are processed threshold images of wear debris. But it is needed to analyse and identify a morphology of wear debris in order to predict and estimate a operating condition of the lubricated machine. If the morphological characteristics of wear debris are identified by the computer image analysis and the neural network, it is possible to recognize the friction condition. In this study, wear debris in the lubricating oil are extracted from membrane filter (0.45 ${\mu}m$) and the quantitative value fur shape parameters of wear debris was calculated through the computer image processing. Four shape parameters were investigated and friction condition was recognized very well by the neural network.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.136-142
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• 2003

The morphological analysis of wear debris can provide early a failure diagnosis in lubricated moving system. It can be effective to analyze operating conditions of oil-lubricated tribological system with shape characteristics of wear debris in a lubricant. But, in order to predict and recognize an operating condition of lubricated machine, it is needed to analyze and to identify shape characteristics of wear debris. Therefore, If the morphological characteristics of wear debris are recognized by computer image analysis using the neural network algorithm, it is possible to recognize operating condition of hydraulic driving members. In this study, wear debris in the lubricating oil are extracted by membrane filter (0.45 ${\mu}{\textrm}{m}$), and the quantitative values of shape parameters of wear debris are calculated by the digital image processing. This shape parameters are studied and identified by the artificial neural network algorithm. The result of study could be applied to prediction and to recognition of the operating condition of hydraulic driving members in lubricated machine systems.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.109-112
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• 2000

고역의 주파수 성분이 감쇠되어 선명도가 저하된 이미지나 선형 보간법에 의해 확대된 이미지의 계단모양 왜곡을 감소시킴으로써 경계선의 선명도가 저하된 이미지들을 위해 형태학적 처리(morphological processing)에 의한 이미지 윤곽선의 선명도를 향상시키는 방법을 제안하였다. 본 논문에서는 블러링(blurring)된 이미지를 화소의 명암에 따라 다수개의 평판 이미지(slice image)로 나누고 각 평판 이미지에 대해 반복적인 최대/최소값 필터(min/max filter)의 적용으로 얻어진 윤곽선의 중심을 기준으로 하여 팽창(dilation)과 침식(erosion)을 수행함으로 이미지의 윤곽선에서의 명암 변화에 대한 경사도를 크게 만들고 이로써 이미지 윤곽선의 선명도를 향상시키는 방법을 사용하였으며 모의 시험결과를 통하여 고역 주파수 강조에 의한 방법에 비하여 인위적인 잡음(artifact)없이 효과적으로 선명도를 향상시킬 수 있음을 보였다.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.141-148
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• 2021

In this paper, we propose an algorithm of welding bead detection and evaluation using geodesic active contour algorithm and high pass filter with image processing technique. The algorithm uses histogram equalization and high pass filter as gaussian filter to improve contrast. The image processing techniques smoothens the welding beads reduce the noise on an image. Then, the algorithm detects the welding bead area by applying the geodesic active contour algorithm and morphological ooperation. It also applies the balloon force that either inflates in, or deflates out the evolving contour for a better segmentation. After that, we propose a method for determining the quality of welding bead using effective length and width of the detected bead. In the experiments, our algorithm achieved the highest recall, precision, F-measure and IOU as 0.9894, 0.9668, 0.9780, and 0.8957 respectively. We compared the proposed algorithm with the conventional algorithms to evaluate the performance of the proposed algorithm. The proposed algorithm achieved better performance compared to the conventional ones with a maximum computational time of 0.6 seconds for segmenting and evaluating one welding bead.

• Textile Coloration and Finishing
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• v.34 no.1
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• pp.20-26
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• 2022

Centrifugal spinning is an emerging technique for fabricating micro-to-nano-fibers in recent years. To obtain fibers with the desired size and morphology, it is necessary to configure and optimize the parameters used in centrifugal spinning. In this study, it was controlled by changing the solution's concentration (7.5, 10, and 12.5 wt.%) and disk's rotational velocity (6,000, 8,000, and 10,000 rpm) to prepare centrifugal spun nano-filter. The morphological property, air permeability, and dust collection efficiency of the PVA/PP bi-layer nanoweb prepared by centrifugal spun PVA on the PP micron nonwoven substrate are studied using a field emission scanning electron microscope, an air permeability tester, and a filter tester equipment, and the analysis results indicate that it is suitable as a nano-filter when the concentration of PVA solution is 10 wt.% and the rotational velocity of the disk is 8,000 rpm. The resultant reduced diameter and uniform fibers also proved that an excellent dust collection efficiency filter could be made.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.578-585
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• 2018

In this paper, we propose a classification and theft detection system for human and livestock for various moving objects in a barn. To do this, first, we extract the moving objects using the GMM method. Second, the noise generated when extracting the moving object is removed, and the moving object is recognized through the labeling method. And we propose a method to classify human and livestock using model formation and color for the unique form of the detected moving object. In addition, we propose a method of tracking and overlapping the classified moving objects using Kalman filter. Through this overlap determination method, an event notifying a dangerous situation is generated and a theft determination system is constructed. Finally, we demonstrate the feasibility and applicability of the proposed system through several experiments.

• Journal of Microbiology and Biotechnology
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• v.8 no.1
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• pp.49-52
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• 1998

A fungal strain able to produce filter paper activity (FPase) was isolated from soil by testing the ability to hydrolyze using filter paper. The isolated strain was identified as an Aspergilus sp. judging from its morphological and microscopical characteristics. The cellulase-xylanase system of Aspergillus sp. 8-17 was detected in situ after gel electrophoresis in the presence of SDS and showed that each protein pattern had a distinct polypeptide composition. ${\beta}$-1,4-Glucanase, cellobiohydrolase, and xylanase activity profiles differ from protein patterns. The Aspergillus sp. 8-17 hydrolytic enzymes responsible for the hydrolysis of ${\beta}$-glucan, MUC, and xylan have multiple active forms.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.54-56
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• 2009

We propose an image change detection algorithm implemented on sensor nodes of the ubiquitous sensor network(USN). The proposed algorithm was designed for the robust detection of image changes regardless of the continuously changing ambient illumination environment. Morphological lowpass filter was used for estimating the illumination component in order to reduce computational burden instead of the existing Gaussian lowpass filter. The decision of the change detection is based on the result of threshold of difference image between two consecutive images. We also propose a new thresholding method using precalculated histogram information. The proposed algorithm was implemented on the MSP430 16bit microprocessor.