• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.590-593
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• 2001

In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.127-132
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• 2000

Though the increment of using computer vision system, there are lots of difficulties to measure precisely because of measurement error or distortion phenomenon. Among these reasons, the distortion of edge is dominant reason which is occurred by the blurred image. So, the problem of clear judgment about image focal point is very important. We must fix the discrimination criteria which is collected by image recognition of precise focus. To solve these problems, we compare with make processing methods using image intensity gradient, laplacian, and sum -modified laplacian operator. These experimental results showed modified mask processing method is effective.

• 한국산학기술학회논문지
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• 제14권7호
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• pp.3460-3467
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• 2013

본 논문에서는 2차원 대지구조를 분석하기 위해 ERT(electrical resistance tomography) 방법을 사용하여 대지모델을 영상복원하는 방법들을 수치적인 실험방법들을 통해 비교분석한다. 영상복원을 위한 역산방법으로는 Gauss-Newton, TLS(truncated least squares), 그리고 SIRT(simultaneous iterative reconstruction technieque) 알고리즘들이 제시되고 대지저항을 측정하기 위한 전극법은 대표적인 웨너와 슐럼버거 측정방법을 사용한다. 컴퓨터 시뮬레이션을 통해 Gauss-Newton과 TLS 알고리즘이 대지모델의 2차원 영상복원에서 적합하다는 것을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.541-546
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• 2004

This study compare the coordination and area between cadastral map digital data corrected by normal nap and serial cadastral map edited by formal data. By superposition ortho image made from aerial photo to serial cadastral map, we propose the method to improve the confidence and use the ortho image efficiently in cadastral part.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.19-22
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• 2000

In this paper, we present a new multiple description embedded zerotree wavelet coding method using the two splitted thresholds. We first model a half EZW coder and then we present multiple description coder which has two coding channels using wide threshold EZW(WTEZW) coders. To evaluate the performance of the proposed coder, we provide an image coding applications with two descriptions and compare MDC image coding results reported to date.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 1994년도 종합학술발표회논문집
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• pp.193-202
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• 1994

In this paper, we investigate possible scrambling methods for the JPEG(Joint Photographic Export Group) still image compression standard. In particular, we compare the conventional line rotation and line permutation methods to the DCT block scrambling in terms of the number of bits to be increased and the easiness of buffer control. Computer simulation results show that the DCT block scrambling method is suitable for both data security and buffer control in one-chip JPEG applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.257-271
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• 2016

The Structural SIMilarity (SSIM) index is one of the most widely-used methods for perceptual image quality assessment (IQA). It is based on the principle that the human visual system (HVS) is sensitive to the overall structure of an image. However, it has been reported that indices predicted by SSIM tend to be biased depending on the type of distortion, which increases the deviation from the main regression curve. Consequently, SSIM can result in serious performance degradation. In this study, we investigate the aforementioned phenomenon from a new perspective and review a constant that plays a big role within the SSIM metric but has been overlooked thus far. Through an experimental study on the influence of this constant in evaluating images with SSIM, we are able to propose a new solution that resolves this issue. In the proposed IQA method, we first design a system to classify different types of distortion, and then match an optimal constant to each type. In addition, we supplement the proposed method by adding color perception-based structural information. For a comprehensive assessment, we compare the proposed method with 15 existing IQA methods. The experimental results show that the proposed method is more consistent with the HVS than the other methods.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제5권10호
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• pp.489-496
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• 2016

병리 정보시스템(Pathological Information System: PIS)은 매일 수천 장씩 생산되는 환자 병리 이미지를 관리하는데 활용되고 있으며, 이 이미지 정보들을 어떻게 효과적으로 처리할 것인지는 병리 정보 처리에 있어서 중요한 연구 과제 중 하나이다. 이미지의 외곽선을 추출하는 것은 병리 이미지 처리에 있어 가장 중요한 작업이지만 현재 사용되는 알고리즘은 정확도에 있어 많은 개선점을 가지므로, 본 논문에서는 이미지의 외곽선 검측에 있어서 기존의 Canny 알고리즘의 원리를 바탕으로 적응적 임계값 설정이 가능하며 눈금자를 임계값 설정의 기준으로 삼는 방식을 제안하여 기존 외곽선 추출 방식보다 정확한 방식을 제안한다. 제안 방식은 기존 방식과의 비교실험을 통해 성능을 검증하였으며, 이 실험에서는 임의로 선정된 병리 이미지 군, 기존 방식으로는 식별이 제한되었던 병리 이미지 군 및 의도적으로 노이즈를 추가한 이미지 군을 대상으로 실험하였고, 실험 결과를 비교하여 제안하는 이미지 외곽선 식별 방식의 향상된 성능을 증명했다.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.523-530
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• 2014

Machine material and structural strain are critical factors for appraising mechanical properties and safety. Particularly in three and four-point bending tests, which appraise the deflection and flexural strain of an object due to external force, measurements are made by the crosshead movement or deflection meter of a universal testing machine. The Digital Image Correlation (DIC) method is one of the non-contact measurement methods. It uses the image analyzing method that compares the reference image with the deformed image for measuring the displacement and strain of the objects caused by external force. Accordingly, the advantage of this method is that the object's surface roughness, shape, and temperature have little influence. However, its disadvantage is that it requires extensive time to compare the reference image with the deformed image for measuring the displacement and strain. In this study, an algorithm is developed for DIC that can improve the speed of image analysis for measuring the deflection and strain of an object caused by a three-point bending load. To implement this algorithm for improving the speed of image analysis, LabVIEW 2010 was used. Furthermore, to evaluate the accuracy of the developed fast correlation algorithm, the deflection of an aluminum specimen under a three-point bending load was measured by using the universal test machine and DIC measurement system.