• Current Photovoltaic Research
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• v.6 no.4
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• pp.91-93
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• 2018

Polythiophene-$TiO_2$ composite was synthesized with different molar ratios of thiophene and titaniumisopropoxide ($Ti(OPr)_4$) for flexible solar cell application as a flexible electrode or an active material. The $Ti(OPr)_4$ was stabilized by thiophene. The thiophene was polymerized by ferric chloride catalyst. The synthesized polythiophene exhibited strong UV-visible absorption in the range of the wavelength shorter than 500 nm. Field emission scanning electron microscope (FESEM) image of low concentration of $TiO_2$ film showed smooth surface. However, FESEM image of high concentration of $TiO_2$ film exhibited relatively rough surface. Polythiophene concentration dependent strong photoluminescence quenching of surfrhodamine-B was observed.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.433-438
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• 2014

This study aims to get more accurate and objective result by quantifying the result for the sperm changes through the quantitative analysis by the image processing based on the image obtained microscopically for the testicle cell and sperm change appeared with the passage of time when the radiation is irradiated to the white rat testicle. This study has targeted the white rat of 8 weeks lifespan, the X-ray of 6 MV with 1 time of 2 Gy has been irradiated to the whole body. The testicles of 5 rats at each test group immediately after irradiation, after 2 hours of irradiation, 4 hours, 8 hours and 24 hours has been respectively extracted targeting all 30 white rats of normal control group not irradiated by the radiation and the test group. The state of testicle cell and sperm has been observed in the normal control group and the test group by implementing Periodic acid Schiff dyeing after extraction. 24 hours after irradiation, a gradual decrease in sperm count and testicular cells qualitatively and quantitatively that were identified as significant.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.90-97
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• 1999

Recently, there have been many researches to automate processing and analysing image data in medical field, due to the advance of image processing techniques, the fast communication network and high performance hardware. In this paper, we design and implement the system based on the multi-layer neural network model to be able to analyze, differentiate and count blood cells in the peripheral blood image. To do these, we segment red and white-blood cell in blood image acquired from microscope with CCD(Charge-coupled device) camera and then apply the various feature extraction algorithms to classify. In addition to, we reduce multi-variate feature number using PCA(Principle Component Analysis) to construct more efficient classifier. So, in this paper, we are sure that the proposed system can be applied to a pathological guided system.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.331-335
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• 2008

In this paper, we parallelized a feature point extraction algorithm to reduce panorama image generation time in multi-core environment. While we compose a panorama image with several images, the step to extract feature points of each picture is needed to find overlapped region of pictures. To perform rapidly feature extraction stage which requires much calculation, we developed a parallel algorithm to extract feature points and examined the performance using CBE(Cell Broadband Engine) which is asymmetric multi-core architecture. As a result of the exam, the algorithm we proposed has a property of linear scalability-the performance is increased in proportion the number of processors utilized. In this paper, we will suggest how Image processing operation can make high performance result in multi-core environment.

• Transactions on Electrical and Electronic Materials
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• v.13 no.4
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• pp.212-214
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• 2012

Both the electrically positive and negative particles in a cell of quick response-liquid powder display (QR-LPD) are surrounded by conductive electrodes on the upper and lower substrate and the dielectric materials of the barrier ribs. Particles in a cell are attached to or detached from the other materials by image force, electric field, Coulomb's force, and Van der Waals' force. Through these forces, the moving particles form an image but induce clumping phenomena. Particles having a large kinetic energy by a large q/m value crash into the opposite electrode with high speed at a large driving voltage and quickly lose electrically charged material. As a result, these particles are clumped and degrade panel performance. The clumped particles in a cell are observed by microscopic photographs and ascertained by a response time. When the bias voltage is increased to 0.68-0.76 $V/{\mu}m$, particle clumping occurs abruptly and the response time increases sharply. This particle clumping is similarly observed after the number of driving times at the driving voltage (0.42-0.64 $V/{\mu}m$).

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1837-1851
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• 2016

Newspaper reader mobile applications using text-to-speech (TTS) function enable blind people to read newspaper contents. But, tables cannot be easily read by the reader program because most of the tables are stored as images in the contents. Even though we try to use OCR (Optical character reader) programs to recognize letters from the table images, it cannot be simply applied to the table reading function because the table structure is unknown to the readers. Therefore, identification of exact location of each table cell that contains the text of the table is required beforehand. In this paper, we propose an efficient image processing algorithm to recognize all the cells in tables by identifying columns and rows in table images. From the cell location data provided by the table column and row identification algorithm, we can generate table structure information and table reading scenarios. Our experimental results with table images found commonly in newspapers show that our cell identification approach has 100% accuracy for simple black and white table images and about 99.7% accuracy for colored and complicated tables.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.35-41
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• 2012

We propose a new marker driven Watershed algorithm for automated segmentation of clustered cell from microscopy image with less over segmentation. The Watershed Transform is able to segment extremely complex objects which are highly touched and overlapped each other. The success of the Watershed Transform depends essentially on the finding markers for each of the objects of interest. For extracting of markers positioning around center of each cell we used radial symmetry and iterative voting algorithms. With synthetic and real images, we quantitatively demonstrate the performance of our method and achieved better results than the other compared methods.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.99-106
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• 2007

In this paper, we present an AAW(Adaptive Attention Window) based cell image segmentation method. For semantic AAW detection we create an initial Attention Window by using a luminance map. Then the initial AW is reduced to the optimal size of the real ROI(Region of Interest) by using a quad tree segmentation. The purpose of AAW is to remove the background and to reduce the amount of processing time for segmenting ROIs. Experimental results show that the proposed method segments one or more ROIs efficiently and gives the similar segmentation result as compared with the human perception.

• Journal of Information Display
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• v.8 no.4
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• pp.5-9
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• 2007

We demonstrate an optically compensated bend (OCB) cell with pixel-isolating polymer wall. The polymer wall is formed by anisotropic phase separation of LCs and UV-curable polymer. The fabricated cell is initially in ${\pi}-twisted$ state so that it shows uniform and fast bend transition without any transition nucleus. The proposed cell has lower driving voltage than conventional OCB cell. Also, the polymer wall provides mechanical stability, hence preventing distortion of display image from external pressure.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.36-40
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• 2006

A new method of digital image analysis technique for medical images of cancer cell is presented. This paper deals with the cancer cell discrimination. The object images were the Thyroid Gland cell images that were diagnosed as normal and abnormal. This paper proposes a new discrimination method based on fuzzy logic algorithm. The focus of this paper is an automatic discrimination of cells into normal and abnormal of medical images by dominant feature parameters method with fuzzy algorithm. As a consequence of using fuzzy logic algorithm, the nucleus were successfully diagnosed as normal and abnormal. As for the experimental result, average recognition rate of 64.66% was obtained by applying single parameter of 16 feature parameters at a time. The discrimination rate of 93.08% was obtained by proposed method.