• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.100-102
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• 2003

This system is capable of obtaining quantitative information from images using natural features on the ortho-image maps that correspond with those from topographical maps. However, the qualitative information can also be obtained because because of the excellent visibility of ortho-image maps. There are plenty of promise for the use of ortho-image maps in the next generation topographic technology because of its wider applicability within the field. In keeping with the cutting edge, we produced ortho-image maps by scanning a specified area in narrow sections using the PKNU 2: a multispectral digital aerial photographing system made by ourselves. We evaluated the precision of the ortho-image maps, and performed an evaluation of the PKNU 2 system's capacity to improve the equipment of the PKNU 2. Ortho-image maps were made using Ground Control Points (GCPs) which were obtained from digital maps and aerial photographs of the PKNU 2. Thus, we demonstrated that it was possible to produce the ortho-image maps, which has a good constant level rate of less than 1m. The PKNU 2 system needs to be improving in the sensitivity of level maintenance equipment in the evaluation in terms of performance. It is thus required to survey the GCPs precisely for an accurate study.

• 한국항행학회논문지
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• 제20권4호
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• pp.380-385
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• 2016

그림자는 자연 영상에서 관찰되는 물리적인 현상이지만 위성 영상 분석에 부정적인 영향을 미치는 요소로 컴퓨터 비전의 전처리 과정에서 그림자 검출 과정은 매우 중요하다. 본 논문에서는 싱글 영상 기반의 위성 영상에서 효과적인 영상 분석을 위해 그림자를 검출하는 방법으로 크로스 엔트로피와 밝기 영상을 이용해 그림자를 검출하는 방법을 제안하였다. 칼라 영상을 그레이 레벨 영상으로 변환한 후 크로스 엔트로피를 기반으로 최적의 임계값을 추정하여 첫 번째 그림자 후보 영역으로 판별하였고, 칼라 영상의 밝기 영상을 이용해 최종 그림자 영역을 검출하였다. 제안하는 방법의 타당성을 위해 위성 영상들을 대상으로 실험하였고, 실험 결과 제안하는 그림자를 검출 방법이 효과적으로 수행됨을 확인하였다.

• 대한전자공학회논문지SP
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• 제41권5호
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• pp.135-141
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• 2004

영상 보간은 기존에 존재하는 화소의 정보로 빈 화소를 계산하여 영상을 확대하는 방법이다. 자연 영상은 다양한 공간 주파수 성분을 포함하기 때문에 하나의 영상 보간 방법으로 다양한 주파수 성분에 대한 보간을 모두 수행하기에는 어려운 점이있다. 본 논문에서는 공간 주파수 특성을 가지는 다중 신경회로망 구조를 이용하여 영상을 보간하는 방법은 제안한다. 입력 영상은 국부 분산에 의해 공간 주파수에 따라 분리되어 공간 주파수 대역 별로 설정된 신경회로망을 통하여 보간 된다. 제안 방법은 deinterlacing에서의 적용성 때문에 관심이 커지고 있는 2배의 영상 보간에 적용되었다. 모의 실험에서 제안 방법은 기존의 알고리즘들뿐 아니라 단일 신경 회로망을 사용하는 방법보다 개선된 PSNR 성능을 보여주었다.

• 디지털콘텐츠학회 논문지
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• 제5권4호
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• pp.269-274
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• 2004

필드 기반 영상 모핑은 제어선을 지정하는 과정의 대부분을 사용자의 수작업에 의존하기 때문에 작업 시간이 많이 소요될 뿐만 아니라 양질의 결과를 얻기 위해서는 숙련을 요하는 불편함이 있다. 본 논문은 소스 영상과 목표 영상에서 모핑 대상체 쌍의 형상 정보를 획득한 상태에서 사용자가 수동으로 최소한의 특징점 쌍만을 지정하면 이렇게 지정된 특징점 쌍을 기준 삼아 다각형 기반 정점 탐색에 의해 소스 영상과 목표 영상에 상호 대응되는 제어선들을 자동적으로 설정한 후, 제어선 길이의 비율과 제어선으로부터의 이격 거리를 이용하여 영상 모핑을 수행함으로써 영상 모핑의 반자동화를 실현할 수 있는 방법을 제안한다. 제안된 방법에 따르면, 사용자가 제어선을 설정하는 시간을 단축할 수 있고 비숙련자도 최소의 제어선만을 지정하여 자연스러운 모핑 결과를 획득할 수 있는 이점이 있다.

• Journal of Astronomy and Space Sciences
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• 제30권4호
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• pp.321-326
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• 2013

The modulation transfer function (MTF) is a widely used indicator in assessments of remote-sensing image quality. This MTF method is also used to restore information to a standard value to compensate for image degradation caused by atmospheric or satellite jitter effects. In this study, we evaluated MTF values as an image quality indicator for the Geostationary Ocean Color Imager (GOCI). GOCI was launched in 2010 to monitor the ocean and coastal areas of the Korean peninsula. We evaluated in-orbit MTF value based on the GOCI image having a 500-m spatial resolution in the first time. The pulse method was selected to estimate a point spread function (PSF) with an optimal natural target such as a Seamangeum Seawall. Finally, image restoration was performed with a Wiener filter (WF) to calculate the PSF value required for the optimal regularization parameter. After application of the WF to the target image, MTF value is improved 35.06%, and the compensated image shows more sharpness comparing with the original image.

• Current Optics and Photonics
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• 제8권3호
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.

• 한국지반신소재학회논문집
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• 제16권4호
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• pp.191-210
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• 2017

The concern study, present the results of experimental study on the performance of deep excavation by using image processing technique particle image velocimetry (PIV). The purpose of present study is to check the application of PIV for the successive ground deformation during deep excavation. To meet the objectives of concern study, a series of reduce scale model test box experiments are performed by considering the wall stiffness, ground water table effect and ground relative density. The results are presented in form of contour and vector plots and further based on PIV analysis wall and ground displacement profile are drawn. The results of present study, indicate that, the PIV technique is useful to demonstrate the ground deformation zone during the successive ground excavation as the degree of accuracy in PIV analysis and measured results with LVDT are within 1%. Further the vector and contours plot effectively demonstrate the ground behavior under different conditions and the PIV analysis results fully support the measured results.

• 한국지반신소재학회논문집
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• 제17권3호
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• pp.33-46
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• 2018

본 논문에서는 대심도 굴착시 흙막이 벽체에 대한 실내 모형실험 결과를 다루었다. 지반의 지하수위와 벽체의 강성등의 영향인자가 흙막이 벽체 및 지반 거동에 미치는 영향에 대한 정성적 고찰을 위하여 기존 CIP 벽체와 CS-H벽체의 휨강성에 따른 상사법칙을 적용하여 제작 및 사용하여 모형실험을 수행하였으며, 실제 현장을 모사하여 버팀보 설치 및 굴착을 진행하였다. 또한 벽체, 지반 거동 분석을 위하여 PIV 분석을 수행하였으며, 벽체변위, 지반침하 및 지반 수평변위를 분석하여 지하수위가 높아질수록 벽체 강성이 작아질수록 변위가 커지는 것을 확인하였다.

• 한국의류학회지
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• 제24권1호
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• pp.128-137
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• 2000

A range of suede-like samples were collected including woven fabric type, nonwoven fabric type, and natural suede(sheep). The surface textures of these suede-like fabrics are rather diverse and different from the plain filament type fabrics since there are a lot of fine surface free fiber ends. Physical and mechanical measurements were carried using the KES equipments. Based on the Kawabata-Niwa translational equation, primary hand values and THV were calculated. Uniaxial tensile tests were performed. Using glossmeter, the reflectance pattern was analyzed at different incidence and receiving angles. In order to capture the surface images of the specimens, a CCD camera and frame grabber connected to a PC were employed. The reflectance uniformity of the images was measured with line-profile analysis and standard deviation values of the profile of the images were calculated. After the multiscale wavelet transfermation, correlation among the transformed image was analyzed at each scale. The reflectance uniformity of the natural suede was better than that of nonwoven type suede, while that of woven type suede was the last among the selected three samples(natural suede, nonwoven type, woven type). The correlation analysis among images has shown the possibility of using the wavelet transformation of the images as one of the measures to detect similarities among the textured specimens.