• Journal of The Korean Astronomical Society
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• v.38 no.4
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• pp.463-470
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• 2005

In this paper, we have made the component-based development of observational software for KASI solar imaging spectrograph (KSIS) that is able to obtain three-dimensional imaging spectrograms by using a scanning mirror in front of the spectrograph slit. Since 2002, the KASI solar spectrograph has been successfully operated to observe solar spectra for a given slit region as well as to inspect the response functions of narrow band filters. To improve its capability, we have developed the KSIS that can perform sequential observations of solar spectra by simultaneously controlling the scanning mirror and the CCD camera via Visual C++. Main task of this paper is to introduce the development of the component-based software for KSIS. Each component of the software is reusable on the level of executable file instead of source code because the software was developed by using CBD (component-based development) methodology. The main advantage of such a component-based software is that key components such as image processing component and display component can be applied to other similar observational software without any modifications. Using this software, we have successfully obtained solar imaging spectra of an active region (AR 10708) including a small sunspot. Finally, we present solar $H{\alpha}$ spectra ($6562.81{\AA}$) that were obtained at an active region and a quiet region in order to confirm the validity of the developed KSIS and its software.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.415-425
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• 2002

In this paper, we present a content-based image retrieval method which is based on the feature extraction in the wavelet transform domain. In order to overcome the drawbacks of the feature vector making up methods which use the global wavelet coefficients in subbands, we utilize the energy value of wavelet coefficients, and the shape-based retrieval of objects is processed by moment which is invariant in translation, scaling, rotation of the objects The proposed methods reduce feature vector size, and make progress performance of classification retrieval which provides fast retrievals times. To offer the abilities of region-based image retrieval, we discussed the image segmentation method which can reduce the effect of an irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The region-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2013-2017
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• 2013

Background: To compare the effects of two adjuvant chemotherapy regimens, anthracycline-based and cyclophosphamide, methotrexate, fluorourical (CMF) on disease free survival for breast cancer patients in the Eastern Mediterranean region and Asia. Methods: In a systematic review with a multivariate mixed model meta-analysis, the reported survival proportion at multiple time points in different studies were combined. Our data sources were studies linking the two chemotherapy regimens on an adjuvant basis with disease free survival published in English and Persian in the Eastern Mediterranean region and Asia. All survival curves were generated with Graphdigitizer software. Results: 14 retrospective cohort studies were located from electronic databases. We analyzed data for 1,086 patients who received anthracycline-based treatment and 1,109 given CMF treatment. For determination of survival proportions and time we usesb the transformation Ln (-Ln(S)) and Ln (time) to make precise estimations and then fit the model. All analyses were carried out with STATA software. Conclusions: Our findings showed a significant efficacy of anthracycline-based adjuvant therapy regarding disease free survival of breast cancer. As a limitation in this meta-analysis we used studies with different types of anthracycline-based regimens.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.892-903
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• 2018

The paper proposes a novel gait recognition algorithm based on feature fusion of gait energy image (GEI) dynamic region and Gabor, which consists of four steps. First, the gait contour images are extracted through the object detection, binarization and morphological process. Secondly, features of GEI at different angles and Gabor features with multiple orientations are extracted from the dynamic part of GEI, respectively. Then averaging method is adopted to fuse features of GEI dynamic region with features of Gabor wavelets on feature layer and the feature space dimension is reduced by an improved Kernel Principal Component Analysis (KPCA). Finally, the vectors of feature fusion are input into the support vector machine (SVM) based on multi classification to realize the classification and recognition of gait. The primary contributions of the paper are: a novel gait recognition algorithm based on based on feature fusion of GEI and Gabor is proposed; an improved KPCA method is used to reduce the feature matrix dimension; a SVM is employed to identify the gait sequences. The experimental results suggest that the proposed algorithm yields over 90% of correct classification rate, which testify that the method can identify better different human gait and get better recognized effect than other existing algorithms.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.176-181
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• 2023

During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.47-52
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• 2007

Conventional pixel based region segmentation methods have problems of long processing time and incorrect region split on account of performing region split through comparison of neighboring pixels. In this paper, we propose the method which segments a large size of satellite image effectively using modified centroid linkage method. This method is a sort of region split and merge. The proposed method merges pixels and makes them as a new region through only two directional comparing the current positioning pixel with neighbor ones, if they are satisfied with given conditions. Therefore, this method has less comparing time than the cases of previous ones. The experimental result shows that the proposed method is very efficient because of having less processing time and more exact segmented regions than the previous ones.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.194-202
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• 2003

To convert printed images into electronic ones automatically, it requires region analysis of document images and character recognition. In these, regional analysis segments document image into detailed regions and classifies thee regions into the types of text, picture, table and so on. But it is difficult to classify the text and the picture exactly, because the size, density and complexity of pixel distribution of some of these are similar. Thu, misclassification in region analysis is the main reason that makes automatic conversion difficult. In this paper, we propose region analysis method that segments document image into text and picture regions. The proposed method solves the referred problems using one dimensional median filter based method in text and picture classification. And the misclassification problems of boldface texts and picture regions like graphs or tables, caused by using median filtering, are solved by using of skin peeling filter and maximal text length. The performance, therefore, is better than previous methods containing commercial softwares.

• Journal of KIISE
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• v.44 no.10
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• pp.1094-1104
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• 2017

In this paper, a motion image is detected based on the irregularity of lights. This motion image is extracted by modifying the reflected light region of the 3 way-diff algorithms. 3 way-diff algorithm extracts reflected light region using the 3-successive image. In this algorithm, The reflected light region is a region generated by light in the image production process and is finally created around all objects. The algorithm shows a process to extracting the region. This process is a simple operation, but doesn't have a defined formula for light. This paper judges that the reflected light region is a kind of noise at the 3 way-diff algorithms and defines the formula for extracting the reflected light region. It shows that compared with the proposed algorithm and existing algorithm through experiment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.30-36
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• 2006

In this paper, a new type of written image segmentation based on relative comparison of region areas is proposed. The original image is composed of two distinctive regions; information and background. Compared with this binary original image, the observed one is the gray scale which is represented with complex regions with speckles and noise due to degradation or contamination. For applying threshold or statistical approach, there occurs the region-deformation problem in the process of binarization. At first step, the efficient iterated conditional mode (ICM) which takes the lozenge type block is used for regions formation into the binary image. Secondly the information region is estimated through selecting action and restored its primary state. Not only decision of the attachment to a region but also the calculation of the magnitude of its area are carried on at each current pixel iteratively. All region areas are sorted into a set and selected through the decision parameter which is obtained statistically. Our experiments show that these approaches are effective on ink-rubbed copy image (拓本 'Takbon') and efficient at shape restoration. Experiments on gray scale image show promising shape extraction results, comparing with the threshold-segmentation and conventional ICM method.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.633-640
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• 2005

In this paper, we propose an adaptive face region extraction algorithm based on skin color information. It consists oi the extraction of face candidate region and projection step. In the step of face candidate region extraction, we extract the pixels which are regarded as the candidate skin color pixels by using the given range. Then, the ratio between the total pixels and the extracted pixels is calculated. According to the ratio, we adaptively decide the range of the skin color and extract face candidate region. In the projection step, we project the extracted face candidate region into vertical direction to estimate the width of the face. Then the redundant parts are efficiently removed by using the estimated face width. And the extracted face width information is used at the horizontal projection step to extract the height of the face. From the experiment results for the various images, the proposed algorithm shows more accurate results than the conventional algorithm.