• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.3
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• pp.1114-1122
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• 1996

Variation of temperature field in a Hele-Shaw convection cell was measured by using a HSI true color image processing system and TLC(Thermochromic Liquid Crystal) solution. The relationship between the hue value of TLC color image and real temperature was obtained and this calibration result was used to measure the true temperature. The temperature field in the Hele-Shaw convection cell shows periodic characteristics of 45 sec at Ra = 9.3 * 10$\^$6/. The temperature field measurement technique developed in this study was proved to be a useful and powerful tool for analyzing the unsteady thermal fluid flows.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.740-747
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• 2017

A fast cell contour extraction method using CUDA parallel processing technique is presented. The cell contour extraction is one of important processes to analyze cell information in pathology. However, conventional sequential contour extraction methods are slow for a huge high-resolution medical image, so they are not adequate to use in the field. We developed a parallel morphology operation algorithm to extract cell contour more quickly. The algorithm can create an inner contour and fail to extract the contour from the concave part of the cell. We solved these problems by subdividing the contour extraction process into four steps: morphology operation, labeling, positioning and contour extraction. Experimental results show that the proposed method is four times faster than the conventional one.

• The Journal of Bigdata
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• v.4 no.1
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• pp.53-61
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• 2019

The extracellular matrix, which provides the structural and biochemical support of surrounding cells, is a cell physiological modulator that controls cell division and differentiation. In the bio sector, the company produces Scapold, a three-dimensional support for tissue engineering, and cultivates stem cells in the produced Scapold to be transplanted into animals to assess tissue regeneration. This depends on components such as collagen in the tissue. Therefore, it is very important to identify the inclusion rate and distribution of components in the tissue, and the data are obtained by analyzing the color of the dyed tissue image. The process from image collection to analysis is costly, and the data collected and analyzed are managed in different formats by different research institutions. Therefore, data integration management and analysis results search are not being performed. In this paper, we establish a database that can manage relevant bigdata in an integrated manner, and propose a bio-image integrated management and retrieval system that can be searched based on color, an important analytical measure in this field of study.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.55-63
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• 2013

Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.

• Journal of Biosystems Engineering
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• v.22 no.4
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• pp.433-438
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• 1997

The freshness of apple was evaluated by characterizing the surface texture of flesh cells. The freshness index which was related to the amount of wrinkles on the cell surface was defined to quantify the freshness. Four parameters relevant to the amount of the cell wrinkles were selected and measured using image analysis including wrinkle extraction procedure and Fast Fourier Transform of a wrinkle-extracted image. Out of 4 parameters, three parameters had highly significant correlations with the time elapsed after harvest. But it was concluded that two parameters out of such 3 parameters could be used for description of freshness index.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.106-108
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• 1989

A new method of digital image analysis technique for discrimination of cancer cell was presented in this paper. The object image was the Thyroid eland cells image that was diagnosed as normal and abnormal (two types of abnormal: follicular neoplastic cell, and papillary neoplastic cell), respectively. By using the proposed region segmentation algorithm, the cells were segmented into nucleus. The 16 feature parameters were used to calculate the features of each nucleus. A9 a consequence of using dominant feature parameters method proposed in this paper, discrimination rate of 91.11% was obtained for Thyroid Gland cells.

• Journal of Biomedical Engineering Research
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• v.33 no.4
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• pp.169-176
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• 2012

Tumor cell morphology is closely related to its migratory behaviors. An active tumor cell has a highly irregular shape, whereas a spherical cell is inactive. Thus, quantitative analysis of cell features is crucial to determine tumor malignancy or to test the efficacy of anticancer treatment. We use 3D time-lapse phase-contrast microscopy to analyze single cell morphology because it enables to observe long-term activity of living cells without photobleaching and phototoxicity, which is common in other fluorescence-labeled microscopy. Despite this advantage, there are image-level drawbacks to phase-contrast microscopy, such as local light effect and contrast interference ring. Therefore, we first corrected for non-uniform illumination artifacts and then we use intensity distribution information to detect cell boundary. In phase contrast microscopy image, cell is normally appeared as dark region surrounded by bright halo ring. Due to halo artifact is minimal around the cell body and has non-symmetric diffusion pattern, we calculate cross sectional plane which intersects center of each cell and orthogonal to first principal axis. Then, we extract dark cell region by analyzing intensity profile curve considering local bright peak as halo area. Finally, we calculated the Fourier descriptor that morphological characteristics of cell to classify tumor cells into active and inactive groups. We validated classification accuracy by comparing our findings with manually obtained results.

• Korean Journal of Optics and Photonics
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• v.17 no.6
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• pp.519-524
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• 2006

In general, the Lohmann-type binary hologram represents its amplitude and phase by using the rectangular cell. In this paper, we adapts a circular cell to represents the amplitude and phase of holograms. In order to compare the characteristics of the circular cell with the rectangular one, we analyzed the results based on the computer simulations and various optical experiments. The results show that a clearer reconstructed image can be obtained by dividing one cell into many pixels. In the case of a uniform reconstructed image, the rectangular cell is better than the circular cell. However, as for the brightness of the reconstructed image, the circular cell is better than the rectangular one.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1150-1159
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• 2014

This paper proposes a method for extracting tissue cells from an organism image by an electron microscope and getting the whole cell number and the area from the cell. In general, the difference between the cell color and the background is used to extract tissue cell. However, there may be a problem when overlapped cells are seen as a single cell. To solve the problem, we split them by using cell size and curvature. This method has a 99% accuracy rate. To measure the cell area, we compute two areas, the inside and boundary of the cell. The inside is simply calculated by the number of pixels. The cell boundary is obtained by applying super sampling, linear interpolation, and cubic spline interpolation. It improves the error rate, 18%, 19%, and 120% respectively, in comparison to the counting method that counts a pixel area as 1.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.