• Journal of Ecology and Environment
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• v.29 no.5
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• pp.425-432
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• 2006

The tadpoles of 12 Korean anuran species, including Bombina orientalis, Bufo gargarizans, B. stejnegeri, Hyla japonica, Kaloula borealis, Rana dybowskii, R. huanrenensis, R. coreana, R. nigromaculata, R. chosenica, R. rugosa, and R. catesbeiana, were classified based on their morphological characteristics. We collected eggs or tadpoles of the 12 Korean anuran species from Gangwon, Incheon, Chungcheong, and Gyeonggi districts in 2005 and 2006 breeding seasons. When the tadpoles reached at $27{\sim}37$ Gosner's developmental stages, we described morphological characteristics of the tadpoles of each anuran species and measured their physical parameters such as total length, body length, and body mass. After that, we chose 12 morphological characteristics to identify each species and to use them as classification keys such as eye location, caudal musculature pattern, spiracle location, oral disc morphology, and labial tooth row formula. In this paper, we presented classification keys, morphological characteristics, and drawings for the tadpoles of 12 anuran species.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.9-17
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• 2017

Hyperspectral imagery is used in the land cover classification with the principle component analysis and minimum noise fraction to reduce the data dimensionality and noise. Recently, studies on the supervised classification using various features having spectral information and spatial characteristic have been carried out. In this study, principle component bands and normalized difference vegetation index(NDVI) was utilized in the supervised classification for the land cover classification. To utilize additional information not included in the principle component bands by the hyperspectral imagery, we tried to increase the classification accuracy by using the NDVI. In addition, the extended attribute profiles(EAP) generated using the morphological filter was used as the input data. The random forest algorithm, which is one of the representative supervised classification, was used. The classification accuracy according to the application of various features based on EAP was compared. Two areas was selected in the experiments, and the quantitative evaluation was performed by using reference data. The classification accuracy of the proposed algorithm showed the highest classification accuracy of 85.72% and 91.14% compared with existing algorithms. Further research will need to develop a supervised classification algorithm and additional input datasets to improve the accuracy of land cover classification using hyperspectral imagery.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.15-21
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• 2015

This study proposed a Sasang constitution classification system that can increase the objectivity and reliability of Sasang constitution diagnosis using the image of frontal face, in order to solve problems in the subjective classification of Sasang constitution based on Sasang constitution specialists' experiences. For classification, characteristics indicating the shapes of the eyes, nose, mouth and chin were defined, and such characteristics were extracted using the morphological statistic analysis of face images. Then, Sasang constitution was classified through a SVM (Support Vector Machine) classifier using the extracted characteristics as its input, and according to the results of experiment, the proposed system showed a correct recognition rate of 93.33%. Different from existing systems that designate characteristic points directly, this system showed a high correct recognition rate and therefore it is expected to be useful as a more objective Sasang constitution classification system.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.545-552
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• 1996

Researches on chromosome are very significant in cytogenetics since a gene of the chromosome controls revelation of the inheritance plasma The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, we propose an algorithm for reconstruction of the chromosDme image to improve the chromosome classification accuracy. Morphological feature parameters are extracted from the reconstructed chromosome images. The reconstruction method from chromosome image is the 32 direction line algorithm. We extract three morphological feature parameters, centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.), by preprocessing ten human chromosDme images. The experimental results show that proposed algorithm is better than that of other researchers'comparing by feature parameter errors.

• KSTLE International Journal
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• v.2 no.1
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.102.2-102.2
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• 2011

Sunspots usually appear in a group which can be classified by certain morphological criteria. In this study we examine the moments which are statistical parameters computed by summing over every pixels of contours, in order to quantify the morphological characteristics of a sunspot group. The moments can be additional characteristics to the sunspot group classification such as McIntosh classification. We are developing a program for image processing, detection of contours and computation of the moments using continuum images from SOHO/MDI. We apply the program to count the sunspot numbers from 303 continuum images in 2003. The sunspot numbers obtained by the program are compared with those by SIDC. The comparison shows that they have a good correlation (r=89%). We are extending this application to automatic sunspot classification (e.g., McIntosh classification) and flare forecasting.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.69.1-69.1
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• 2011

While the Virgo Cluster Catalog (VCC) is well established catalog from deep photographic plate survey, with available survey data recently released (e.g., SDSS), it can be further updated concerning the membership and morphology of galaxies. While membership and morphology of galaxies included in the VCC are based on the single band imaging data, thanks to the multi-color imaging and spectroscopic observations of SDSS, we are able to revise the membership and morphology of sample galaxies in the fields of the Virgo cluster. We present a new catalog of galaxies in the Virgo cluster using SDSS DR7 data, the extended Virgo cluster catalog. Using SDSS imaging and spectroscopic data, we introduce two kinds of galaxy classifications which are complementary each other. In addition to traditional morphological classification by visual inspection of the images ("Primary Classification"), we also attempt to classify galaxies with the spectroscopic features ("Secondary Classification"). The primary classification is basically based on the scheme of galaxy morphological classification of VCC. The secondary classification relies on the SED shape and presence of emission/absorption lines returned from SDSS. Our morphological classifications allow to study the evolution and associated star formation histories of galaxies in the Virgo cluster.

• Korean Journal of Plant Resources
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• v.19 no.1
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• pp.105-111
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• 2006

The objectives of this study, an analysis of fruit and leaf morphological characteristics among the five Zizyphus cultivars could be used for the investigation of cultivars classification and could provide information to make out the UPOV TG(Test Guidelines). ANOVA tests showed that there were statistically significant differences in all fruit and leaf morphological characteristics among the five Zizyphus cultivars at 1% level. But, for kernel characteristics, differences were statistically non-significant among the cultivars. Approximately, the Wolchul and Boeun cultivars showed larger and smaller values in overall characteristics and cultivars, respectively. The results of principal component analysis(PCA) for the fruit and leaf morphological characteristics showed that the first for principal components(PC's) explained about 65.3% of the total variation. The first PC was correlated with those characteristics that were mainly related to the terminal leaf length(TLL), leaf length(LL), fruit length(FL), terminal leaf width(TLW), and leaf petiole length(LPL). The second and third PC was mainly correlated with the terminal leaf morphological index(TLMI). Therefore, these characteristics were important to analysis of the fruit and leaf morphological characteristics and classification among the five Zizyphus cultivars. Cluster analysis using UPGMA method based on principal components showed that five Zizyphus cultivars could be clustered into two groups. Group I comprises Mudung, Wolchul, and Bokjo and Geumsung cultivars, Group II is Boeun cultivar. These results well similar to that of principal component analysis.

• Smart Media Journal
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• v.5 no.4
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• pp.103-110
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• 2016

This study aims to establish the standards to give the design weight in case when developing equipment designs, by classifying products with similar purposes in accordance with the morphological characteristics and also extracting the typicality. Limiting the sampling group for the extraction of the typicality to a pendant-type and a ceiling buried-type through the preceding case study and consultation with experts, the survey was conducted for majors and relevant workers in six cities, sampling products released in Korea and Japan before May 2016. The 1st survey was about the Morphological classification, and the 2nd times about the extraction of the typicality while the 3rd one was about the classification of the morphological attributes. By drawing the design attributes based on the functional/morphological classification and formative principles, it aimed to establish the base of the future research on the measurement of design weight. The results of this study aim to efficiently establish the roles of design technology in accordance with changes in the lighting fixture market caused by the substitution of light sources, and also to draw the development direction to rapidly cope with the accelerated changes in lighting design types and corporate R&D.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.516-517
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• 2015

The automatic traffic sign detection and recognition has been one of the highly researched and an important component of advanced driver assistance systems (ADAS). They are designed especially to warn the drivers of imminent dangers such as sharp curves, under construction zone, etc. This paper presents a traffic sign recognition (TSR) system using morphological operations and multiple descriptors. The TSR system is realized in three stages: segmentation, shape classification and recognition stage. The system is designed to attain maximum accuracy at the segmentation stage with the inclusion of morphological operations and boost the computation time at the shape classification stage using MB-LBP descriptor. The proposed system is tested on the German traffic sign recognition benchmark (GTSRB) and on Korean traffic sign dataset.