• Journal of the Korean Society of Visualization
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• v.13 no.3
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• pp.15-19
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• 2015

We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• Fibers and Polymers
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• v.7 no.1
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• pp.73-78
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• 2006

The ability to absorb liquid and the dust removal performance are important factors for wiping cloths used to remove contaminants. We have developed a method that can determine the contaminant removal performance of wiping cloths. In the gravimetric method, experimental errors are unavoidable because the contaminant plate is much heavier than the contaminant material. However, we used image analysis to reduce the experimental errors, and did not use the heavy contaminant plate. The correlation coefficient between the image. analysis and the gravimetric methods was very high, at R=0.97, with a significance level of 95%. From the correlation analysis and empirical data, the image analysis method is a useful tool for measuring wiping efficiency. The wiping efficiency measured using image analysis has a close relationship to the wiping speed, viscosity of the contaminant, and wiping pressure, at the significance level of 95%.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.133-140
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• 2020

This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.

• Journal of the Optical Society of Korea
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• v.7 no.4
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• pp.234-239
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• 2003

Objective methods to assess quantitatively port wine stain (PWS) blanching in response to laser therapy are needed to improve laser therapeutic outcome. Previous studies have attempted to assess objectively PWS color based on point measurement devices. To date, these approaches have typically been limited by a number of factors such as small test area and need for contact. To address these issues, a polarization spectral imaging system and an image analysis method have been developed to evaluate quantitatively erythema and melanin content distribution in skin. The developed polarization spectral imaging system minimizes artifacts such as glaring, shadowing, and non-uniform illumination that interfere with image fidelity. Furthermore, the image analysis method has been employed to get images of skin melanin and erythema indices from the acquired color images for quantitative analysis. Finally, using PWS patient color image, the effectiveness in laser treatment of PWS was evaluated by calculating relative erythema index image that is the relative erythema index of PWS region to the normal region. The developed device and analysis method appears to be a simple and effective method for quantitative analysis of PWS blanching.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.660-664
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• 2006

A novel quantified method based on requirement analysis of image quality to improve display image quality was proposed. Nowadays, the image quality was limited by the poor understanding of the image quality requirement, which led to the critical factors of image quality could not be controlled during display development. Our method was set up to resolve this problem by clarifying the relationship between the image quality level and the effect factors in image processing. Moreover, the subjective factors were eliminated extremely by the image quality quantification. The method was applied in the RPTV development life cycle and its efficiency was demonstrated.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.164-172
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• 2023

The grain size distribution of sand provides crucial information for understanding coastal erosion and sediment deposition. The commonly used sieve analysis for grain size distribution analysis has limitations such as time-consuming processes and the inability to obtain information about individual particle shapes and colors. In this study, we propose a grain size distribution analysis method using smartphone digital images, which is simpler and more efficient than the sieve analysis method. During the image analysis process, we effectively detect particles from relatively low-resolution smartphone digital images by extracting particle boundaries through image gradient calculation. Using samples collected from four beaches in Gyeongsangbuk-do, we compare and validate the proposed boundary extraction image analysis method with the analysis method that does not extract boundaries, against sieve analysis results. The proposed method shows an average error rate of 8.21% at D₅₀, exhibiting a 65% lower error compared to the method without boundary extraction. Therefore, grain size distribution analysis using smartphone digital images is convenient, efficient, and demonstrated accuracy comparable to sieve analysis.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.571-578
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• 1997

The development of new approaches for wheat grain hardness assessment may impact the grain industry in marketing, milling and breeding. This experiment was to develop a new method for fast identification between softness and hardness, and for maintaining germinability of seed after measurement in wheat. Results from the comparisons of accuracy and significance between image analysis and conventional methods(NIRS and textrometer) were summarized. Data obatined from image analysis for grain hardness did not show any difference from those of the conventional methods. The protein content analyzed by micro-Kjeldahl method was significantly correlated with the grain hardness measured by image analysis, textrometer, and NIRS. The analysis for wheat grain hardness using image analysis may be used as an alternative method to the conventional methods. This method also takes the seeds after analysis can be utilized as breeding materials in early generations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.404-406
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• 2002

In this paper, the method of image feature extraction is proposed. This method employ the energy field analysis, outlier removal algorithm and ring projection. Using this algorithm, we achieve rotation-translation-scale invariant feature extraction. The force field are exploited to automatically locate the extrema of a small number of potential energy wells and associated potential channels. The image feature is acquired from relationship of local extrema using the ring projection method.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.10
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• pp.11-18
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• 2018

In this study, the cross-sectional image has been acquired to evaluate the aggregate distribution affecting quality of lightweight aggregate concrete, and through the binarization method, the study is to calculate the aggregate area of upper and lower sections to develop the method to assess the aggregate distribution of concrete. The acquisition of cross-section image of concrete for the above was available from the cross-sectional photography of cleavage tension of a normal test specimen, and an easily accessible and convenient image analysis software was used for image analysis. As a result, through such image analyses, the proportion of aggregate distribution of upper and lower sections of the test specien could be calculated, and the proportion of aggregate area U/L value of the upper and lower regions of concrete cross-section was calculated, revealing that it could be used as the comprehensive index of aggregate distribution. Moreover, through such method, relatively easy image acquisition methods and analytic methods have been proposed, and this indicated that the development of modeling to assess aggregate distribution quantitatively is available. Based on these methods, it is expected that the extraction of fundamental data to reconsider the connectivity with processes in concrete will be available through quality assessment of quantitative concrete.