• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.204-211
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• 2016

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.162-165
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• 2007

Chlorophyll concentration is an important factor for physical oceanography as well as biological oceanography. For these necessity many oceanographic researchers have been investigated it for a long time. But investigation using vessel is very inefficient, on the other hands, ocean color remote sensing is a powerful means to get fine-scale (spatial and temporal scale) measurements of chlorophyll concentration. Geostationary Ocean Color Imager (GOCI), for ocean color sensor, loaded on COMS (Communication, Ocean and Meteorological Satellite), will be launched on late 2008 in Korea. According to the necessity of algorithm for GOCI, we developed chlorophyll algorithm for GOCI in this study. There are two types of chlorophyll algorithms. One is an empirical algorithm using band ratio, and the other one is a fluorescence-based algorithms. To develop GOCI chlorophyll algorithm empirically we used bands centered at 412 nm, 443 nm and 555 nm for the DOM absorption, chlorophyll maximum absorption and for absorption of suspended solid material respectively. For the fluorescence-based algorithm we analyzed in-situ remote sensing reflectance $(R_{rs})$ data using baseline method. Fluorescence Line Height $({\Delta}Flu)$ calculated from $R_{rs}$ at bands centered on 681 nm and 688 nm, and ${\Delta}Flu_{(area)}$ are used for development of algorithm. As a result ${\Delta}Flu_{(area)}$ method leads the best fitting for squared correlation coefficient $(R^2)$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2298-2304
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• 2012

X-ray fluorescence spectrum analysis method can be applied in many areas, including concentration analysis of RoHS elements and heavy metals etc. and we can get analysis results in a relatively short time. Because X-ray fluorescence spectrum has noises and several artifacts that lowers the accuracy of the analysis. This paper analyzes the characteristics of the noise of the X-ray fluorescence spectrum to increase the accuracy of analysis. X-ray fluorescence spectrum have the characteristics of shot noise (Poisson noise), so the noise size is relatively large in the small signal portion and the noise the size is relatively small in the large part of the signal. Existing methods of analysis and to remove noises is a method for general purposes algorithm. Since these algorithm does not reflect these noise characteristics, we get distorted analysis result. We can design efficient noise remove algorithm based on the accurate noise analysis method, and we expect high accuracy results of the elemental concentration analysis result.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.27-32
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• 2016

A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.103-113
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• 2019

Motivation: Polymerized actin-based cytoskeletal structures are crucial in shape, dynamics, and resilience of a cell. For example, dynamical actin-containing ruffles are located at leading edges of cells and have a significant impact on cell motility. Other filamentous actin (F-actin) bundles, called stress fibers, are essential in cell attachment and detachment. For this reason, their mechanistic understanding provides crucial information to solve practical problems related to cell interactions with materials in tissue engineering. Detecting and counting actin-based structures in a cellular ensemble is a fundamental first step. In this research, we suggest a new method to characterize F-actin wrapping fibers from confocal fluorescence image stacks. As fluorescently labeled F-actin often envelope the fibers, we first propose to segment these fibers by diminishing an energy based on maximum flow and minimum cut algorithm. The actual actin is detected through the use of bilateral filtering followed by a thresholding step. Later, concave actin bundles are detected through a graph-based procedure that actually determines if the considered actin filament is enclosing the fiber.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.

• KSBB Journal
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• v.20 no.4
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• pp.299-304
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• 2005

A two-dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E. coli for the production of 5-aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyed using artificial neural networks, i.e. self-organizing map (SOM) and feedforward backpropagation neural network (BPNN).Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process performance, e.g. forecasting the process performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.47-54
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• 2008

In this paper, we propose an auto-detection algorithm of basal cell carcinoma(BCC) from the protophorphyrin IX(PpIX) fluorescence image induced by appling the methyl 5-aminolaevulinate(MAL) ointment-induced protophorphyrin IX(PpIX) to the skin tumour area and then shining the wood lamp on the area. The proposed algorithm first generates 3 mask areas-tumor area, suspected tumor area and tumor free area and then applies local watershed algorithm to the turner and the suspected tumor areas to make small watershed regions that include similar luminance value pixels. Next, small watershed regions are merged by hierarchical queue based fast region merging that uses the difference between the average luminance values of adjacent watershed regions as a region merging criterion and finally BCC regions are detected. 50 tissue samples are acquired from the tumour regions of 10 patients with BCC that are extracted by using the proposed algorithm and are performed pathological examination by expert dermatologist. Experiment result shows the rate of tumor detection from BCC lesion using presurgical in vivo of MAL-indeuced PpIX fluorescence has high sensitivity 94.1% and relatively high specificity 82.6%.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.2
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• pp.148-156
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• 2007

The fiber dispersion in fiber-reinferced cementitious composites is a crucial factor with respect to achieving desired mechanical performance. However, evaluation of the fiber dispersion in the composite PVA-ECC (polyvinyl alcohol-engineered cementitious composite) is extremely challenging because of the low contrast of PVA fibers with the cement-based matrix. In the present work, a new evaluation method is developed and demonstrated. Using a fluorescence technique on the PVA-ECC, PVA fibers are observed as green dots in the cross-section of the composite. After capturing the fluorescence image with a charged couple device (CCD) camera through a microscope, the fiber dispersion is evaluated using an image processing technique and statistical tools. In this image processing technique, the fibers are more accurately detected by employing an enhanced algorithm developed based on a discriminant method and watershed segmentation. The influence of fiber orientation on the fiber dispersion evaluation was also investigated via shape analyses of fiber images.

• Progress in Medical Physics
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• v.12 no.1
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• pp.9-17
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• 2001

The prior purpose of this study is to introduce a optical biopsy and evaluate whether the optical biopsy, real-time, non-invasive technique, is a reliable tool to assess response to radiotherapy Four healthy volunteers, and four patients with inflammatory conditions of the oral cavity participated on the study. was obtained from each person enrolled in the study. Using FastEEM(Ercited Emission Matrix) as a optical biopsy tool, normal and tumor spectra are taken from the normal and the tumor regions. And then second optical biopsy are taken from the tumor regions in 4 patients with time delay at 7days.. Using a diagnostic algorithm, made by Gillenwater based on spectra excited at 337nm The Optical Biopsy turned out to be more suited for tumor diagnostic resulting in significant difference fluorescence spectra. The fluorescence intensity of cancerous tissue showed a higher position. The second fluorescence intensity of optical biopsy of cancerous oral tissue has more smaller than the first result. I conclude that optical biopsy, which technique don't need to remove tissue sample from body, and is a real time , and non-invasive measurement is a reliable tool to access to radiotherapy because FastEEM can do measure the variation of the tissue composition chemical, biological, and morphological after radiotherapy. Based on the fluorescence spectrum are taken from the optical biopsy in normal and tumor spectra as well as tumor spectra after 7days.