• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.985-988
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• 2007

본 논문에서는 unsharp masking를 이용한 영상 개선 기법을 제안한다. 이 기법은 기존의 unsharp mask을 이용한 영상 개선을 어렵게 만드는 요인 중 하나인 인자를 자동으로 설정하여 이미지를 선명하게 만드는 기법이다. 기존의 세 인자인 Threshold, Amount, Radius를 자동으로 최적화하기 위해, 영상의 각 픽셀을 세 가지 그룹으로 분류하고, 그에 따라 unsharp mask의 적용 정도를 달리한다. 사람이 직접 인자를 입력하여 개선된 영상과 제안된 기법으로 개선된 영상의 비교를 통해 영상 개선 정도를 실험, 분석하였다.

• 대한원격탐사학회지
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• 제33권4호
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• pp.437-444
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• 2017

Since land pixels often generate false alarms in ship detection using Synthetic Aperture Radar (SAR), land masking is a necessary step which can be processed by a land area map or water database. However, due to the continuous coastline changes caused by newport, bridge, etc., an updated data should be considered to mask either the land or the oceanic part of SAR. Furthermore, coastal concrete facilities make noise signals, mainly caused by side lobe effect. In this paper, we propose two methods. One is a semi-automatic water body data generation method that consists of terrain correction, thresholding, and median filter. Another is a dynamic land masking method based on water database. Based on water database, it uses a breadth-first search algorithm to find and mask noise signals from coastal concrete facilities. We verified our methods using Sentinel-1 SAR data. The result shows that proposed methods remove maximum 84.42% of false alarms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.

• 한국산학기술학회논문지
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• 제10권6호
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• pp.1229-1236
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• 2009

최소가청역치를 측정하기 위한 기기인 순음청력검사 시스템은 사운드카드를 가진 컴퓨터에서 소프트웨어로 구현될 경우 가격 경쟁력을 가질 수 있다. 본 논문에서는 일반 PC를 기반으로 설계 및 구현된 순음청력검사 시스템을 기술한다. 개발된 PC 기반 순음청력검사 시스템은 기도 및 골도 검사시 지동 차폐 기능도 지원한다. 또한 자가 검사, 자동 검사 및 수동 검사 모드로 구성되는 다중 모드를 제공함으로써 집이나 병원 등 다양한 환경에서 사용될 수 있도록 설계되었다. 본 연구에서는 구현된 시스템의 출력 전압 파형과 출력 음압 측정을 통해 정상적으로 동작함을 검증하였다.

• 한국지능시스템학회논문지
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• 제14권2호
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• pp.222-227
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• 2004

Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.

• 한국산학기술학회논문지
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• 제11권4호
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• pp.1325-1332
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• 2010

미세증가감수지수 검사는 감각신경성난청의 세부 병변을 감별하기 위하여 사용되는 누가현상을 판별하는 검사이다. 본 논문은 PC 기반 소프트웨어로 구현한 미세증가감수지수 검사 소프트웨어를 기술한다. 구현된 소프트웨어는 검사자의 검사 참여 유 무에 따라 수동 검사와 자동 검사의 두 가지 모드를 제공함으로써 경제적인 검사가 진행 될 수 있게 한다. 또 필요할 경우에 자동으로 차폐를 수행한다. 그리고 1dB의 순간 상승음에 대한 검사뿐만 아니라 2dB와 5dB 상승음에 대한 검사도 지원함으로써 보다 정확한 검사 결과를 얻을 수 있도록 한다.

• 융합신호처리학회논문지
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• 제22권2호
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• pp.79-84
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• 2021

AGV에서 가장 중요한 부품은 가이드 센서이며, 이 센서의 대표적인 기능은 정밀한 주행경로 추출이다. 가이드 센서의 정밀도에 낮거나 잘못된 주행 경로를 추출한다면 AGV가 충돌하거나 AGV 제어에서 좌·우 흔들림이 발생되어 적재물이 낙하, 주행경로 이탈 등의 문제가 발생한다. 이러한 문제점을 개선하기 위해 본 연구에서는 다중 마스킹과 무게중심법을 이용한 가이드센서 신호처리 기법을 제안하고 구현하여 그 성능을 평가하였다. 그 결과, 직진경로 및 좌/우 분기 경로 추출의 평균오차가 2.32[mm]를 보였으며, 특히 기존의 무게중심법 보다 27[%]이상의 성능개선을 보였다. 이와 같이 제안된 가이드 센서 신호 처리 기법을 적용한다면 AGV 자세 제어와 주행 안정성이 향상될 것으로 사료된다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.603-607
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• 2003

The judgment of forged passports plays an important role in the immigration control system, for which the automatic and accurate processing is required because of the rapid increase of travelers. So, as the preprocessing phase for the judgment of forged passports, this paper proposed the novel method for the recognition of passport based on the fuzzy binarization and the fuzzy RBF neural network newly proposed. first, for the extraction of individual codes being recognized, the paper extracts code sequence blocks including individual codes by applying the Sobel masking, the horizontal smearing and the contour tracking algorithm in turn to the passport image, binarizes the extracted blocks by using the fuzzy binarization based on the membership function of trapezoid type, and, as the last step, recovers and extracts individual codes from the binarized areas by applying the CDM masking and the vertical smearing. Next, the paper proposed the enhanced fuzzy RBF neural network that adapts the enhanced fuzzy ART network to the middle layer and applied to the recognition of individual codes. The results of the experiment for performance evaluation on the real passport images showed that the proposed method in the paper has the improved performance in the recognition of passport.

• 한국측량학회지
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• 제37권5호
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• pp.351-357
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• 2019

UAV (Unmanned Aerial Vehicle) images can be exploited for rapid forest fire damage assessment by virtue of UAV systems' advantages. In 2019, catastrophic forest fire occurred in Goseong and Sokcho, Korea and burned 1,757 hectares of forests. We visited the town in Goseong where suffered the most severe damage and conducted UAV flights for forest fire damage assessment. In this study, economic and rapid damage assessment method for forest fire has been proposed using UAV systems equipped with only a RGB sensor. First, forest masking was performed using automatic elevation thresholding to extract forest area. Then ExG (Excess Green) vegetation index which can be calculated without near-infrared band was adopted to extract damaged forests. In addition, entropy filtering was applied to ExG for better differentiation between damaged and non-damaged forest. We could confirm that the proposed forest masking can screen out non-forest land covers such as bare soil, agriculture lands, and artificial objects. In addition, entropy filtering enhanced the ExG homogeneity difference between damaged and non-damaged forests. The automatically detected damaged forests of the proposed method showed high accuracy of 87%.

• 지능정보연구
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• 제9권2호
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• pp.1-18
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.