• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.17-27
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• 2021

In this paper, we develop a galaxy image classification method based on hand-crafted features and machine learning techniques. Additionally, we provide an empirical analysis to reveal which combination of the techniques is effective for galaxy image classification. To achieve this, we developed a framework which consists of four modules such as preprocessing, feature extraction, feature post-processing, and classification. Finally, we found that the best technique for galaxy image classification is a method to use a median filter, ORB vector features and a voting classifier based on RBF SVM, random forest and logistic regression. The final method is efficient so we believe that it is applicable to embedded environments.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.125-126
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• 1996

Beijing-Arizona-Taipei-Connecticut (BATC) survey is a long term project to map the spectral energy distribution of various objects using 15 intermediate band filters and aims to cover about 450 sq degrees of northern sky. The SED information, combined with image structure information, is used to classify objects into several stellar and galaxy categories as well as QSO candidates. In this paper, we present a preliminary setup of robust data reduction procedure recently developed at NCU and also briefly discuss general classification scheme: redshift estimate, and automatic detection of variable objects.

• Journal of Korean Elementary Science Education
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• v.27 no.1
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• pp.9-22
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• 2008

The purpose of this study was to investigate the type of classification criterion and the characteristic of classification strategy that appear in pre-service elementary teachers' classification activity. The 4 tasks were developed for classification activity; button as a real things that attribute is prominent, shell as a real things that attribute is less prominent, snow flake as a picture cards that attribute is prominent, and galaxy as a picture cards that attribute is less prominent. The 5 college students who major in elementary education were selected. Data were collected by interview with participants, participants' classification recording paper, investigator's observation of participants' action observation, and videotaped that record participants' subject classification process. Result proved in this study is as following. First, pre-service elementary teachers used 4 qualitative classification criterion of feature, random field, image and secondary property, and used 2 dimension classification criterion of space and quantity. They used single quality classification criterion or combining dimension classification criterion in classification activity. Second, pre-service elementary teachers have classification strategy that apply each various classification criterion, and also classification strategy are different according to subject, but discussed that "anchor" and "priming effect" are important for effective classification. Result of this study is expected to contribute classification research and classification teaching program development.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.579-590
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• 2022

In this study, we aimed to develop a Python-based outer-ring galaxy analysis algorithm according to the data science process. We assumed that the potential users are citizen scientists, including students and teachers. In the actual classification studies using real data of galaxies, a specialized software called IRAF is used, thereby limiting the general public's access to the software. Therefore, an image analysis algorithm was developed for the outer-ring galaxies as targets, which were compared with those of the previous research. The results of this study were compared with those of studies conducted using IRAF to verify the performance of the newly developed image analysis algorithm. Among the 69 outer-ring galaxies in the first test, 50 cases (72.5%) showed high agreement with the previous research. The remaining 19 cases (27.5%) showed differences that were caused by the presence of bright stars overlapped in the line of sight or weak brightness in the inner galaxy. To increase the usability of the finished product that has undergone a supplementary process, all used data, algorithms, Python code files, and user manuals were loaded in GitHub and made available as shared educational materials.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.81-81
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• 2012

Since the ultraviolet (UV) flux of an integrated population is a good tracer of recent star formation activities, UV observations provide an important constraint on star formation history (SFH) in galaxies. We present UV color-magnitude relations (CMRs) of early-type dwarf galaxies in the Virgo cluster, based on Galaxy Evolution Explorer (GALEX) UV data and the Extended Virgo Cluster Catalog (EVCC, Kim, S. in prep.). The EVCC covers an area 5.4 times larger (750 deg2) than the footprint of the classical Virgo cluster catalog by Binggeli and collaborators. We secure 1304 galaxies as members of the Virgo cluster and 526 galaxies of them are new objects not contained in the VCC. Morphological classification of galaxies in the EVCC is based on the optical image ("Primary Classification") and spectral feature ("Secondary Classification") of the SDSS data. We find that dwarf lenticular galaxies (dS0s) show a surprisingly distinct and tight locus separated from that of ordinary dwarf elliptical galaxies (dEs), which is not clearly seen in previous CMRs. The dS0s in UV CMRs follow a steeper sequence than dEs and show bluer UV-optical color at a given magnitude. Most early type dwarf galaxies with blue UV colors (FUV-r < 6 and NUV-r < 4) are identified as those showing spectroscopic hints of recent or ongoing star formation activities. We explore the observed CMRs with population models of a luminosity-dependent delayed exponential star formation history. The observed CMR of dS0s is well matched with models with relatively long delayed star formation. Our results suggest that dS0s are most likely transitional objects at the stage of subsequent transformation of late-type progenitors to ordinary red dEs in the cluster environment. In any case, UV photometry provides a powerful tool to disentangle the diverse subpopulations of early-type dwarf galaxies and uncover their evolutionary histories.