• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.1-8
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• 2010

In this paper, we propose a large scale entertainment system based on gesture recognition for learning Chinese character contents. The system is consisted of parts that forecast user's posture in two infrared images and part that recognize gestures from continuous poses. And we can divide and acquire in front side pose and side pose about one pose in each IR camera. This entertainment system is immersive in nature and convenient for its gestures based controlling system. Also, it can maximize information transmission because induce immersion and interest using two large size displays and various multimedia elements. The learning Chinese character contents can master Chinese character naturally because give interest to user and supply game and education at the same time. Therefore, it can expect synergy effect that can learn playing to user combining with large entertainment system based on gesture recognition.

• Journal of Animal Science and Technology
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• v.59 no.10
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• pp.21.1-21.6
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• 2017

Background: The aim of the study is to evaluate the effectiveness of thermographic monitoring, using the temperature changes of perianal and perivulvar areas for the determination of estrus in Anatolian Shepherd bitches. Fifteen bitches were used in the study. Blood and vaginal smear samples were collected and thermographic monitoring of perianal and perivulvar areas were carried out starting from proestrus to early diestrus. Also, external signs of estrus were investigated. Smear samples were evaluated by light microscopy after Diff-Quik staining method and superficial and keratinized superficial cells were determined as percentage (S + KS%). Progesterone and luteinizing hormone measurements were done by radioimmunoassay. The difference in temperature between perianal and perivulvar areas was evaluated through thermographic images by FLIR ResearchIR Software. Results: According to the results obtained from the study, differences between progesterone and S + KS% were statistically significant (P < 0,05). Although temperature showed increase and decrease with progesterone and S + KS%, the differences were not important statistically (P > 0,05). Serum luteinizing hormone levels did not sign any difference (P > 0,05). Conclusions: As a result, thermographic monitoring alone is not enough for estrus detection in Anatolian Shepherd bitches. However, it can be used to assist the actual estrus detection technique in terms of providing some foreknowledge by evaluating the differences in temperature.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.409-414
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• 1998

To examine the detectability of the aerosol and/or Yellow dust from China crossing over the Yellow sea, three works carried out as follows , Firstly, a comparison was made of the visible(VIS), water vapor(WV), and Infrared(IR) images of the GMS-5 and NOAA/AVHRR on the cases of yellow sand event over Korea. Secondly, the spectral radiance and reflectance(%) was observed during the yellow sand phenomena on April, 1998 in Seoul using the GER-2600 spectroradiometer, which observed the reflected radiance from 350 to 2500 nm in the atmosphere. We selected the optimum wavelength for detecting of the yellow sand from this observation, considering the effects of atmospheric absorption. Finally, the atmospheric radiance emerging from the LOWTRAN-7 radiative transfer model was simulated with and without yellow sand, where we used the estimated aerosol column optical depth ($\tau$ 673 nm) in the Meteorological Research Institute and the d'Almeida's statistical atmospheric aerosol radiative characteristics. The image analysis showed that it was very difficult to detect the yellow sand region only by the image processing because the albedo characteristics of the sand vary irregularly according to the density, size, components and depth of the yellow sand clouds. We found that the 670-680 nm band was useful to simulate aerosol characteristics considering the absorption band from the radiance observation. We are now processing the simulation of atmospheric radiance distribution in the range of 400-900 nm. The purpose of this study is to present the preliminary results of the aerosol and/or Yellow dust detectability using the Ocean Scanning Multispectral Imager(OSMI), which will be mounted on KOMPSAT-1 as the ocean color monitoring sensor with the range of 400-900 nm wavelength.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.86.1-86.1
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• 2011

We are developing a new universal spectropolarimeter on the Domeless Solar Telescope (DST) at the Hida Observatory to realize precise spectropolarimetric observations in a wide range of wavelength in visible and near infrared. The system aims to open a new window of plasma diagnostics by using Zeeman effect, Hanle effect, Stark effect, impact polarization, and atomic polarization for measuring the external magnetic field, electric field, or an anisotropy in the excitation of the atoms. The polarimeter is a successor of formerly developed polarimeter on DST, which make possible to observe a polarization in a photospheric spectral line with polarimetric accuracy of 10-2 (Kiyohara et al. 2004). The new system consists of a 60cm aperture vacuum telescope, a high dispersion vacuum spectrograph, polarization modulator / analyzer composed of a rotating waveplate whose retardation is constant for a wide range of wavelength and Wallaston prism, and a fast and large format CCD camera or IR camera. Spectral images in both orthogonal polarizations are taken simultaneously with a frame rate of ~20Hz while the waveplate rotates continuously in a rate of 1rev./sec. Thus It takes 5 ~ 60 sec to observe polarization with accuracy of 10-3 in a wide wavelength range (400 - 1100nm). We also examined a polarimetric model of the telescope with accuracy of 10-3 to calibrate instrumental polarization on some wavelengths. In this talk, I will focus on the performance of the instrument.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.41.1-41.1
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• 2014

Although the link between activity in the nuclei of galaxy and galactic mergers has been under scrutiny for several years, it is still unclear to what extent and for which populations of active galaxies merger-triggered activity is relevant. The environment of AGN allows an indirect probe of the past merger history and future merger probability of these systems, suffering less from sensitivity issues while extending to higher redshifts, compared to traditional morphological studies of AGN host galaxies. Here we present results from our investigation of the environment of radio selected sources out to redshift z=2. We employ the first data release J-band catalog from the new near-IR Infrared Medium-Deep Survey (IMS) and 1.4 GHz radio data from the Faint Images of the Radio Sky at Twenty-cm (FIRST) survey and a deep dedicated VLA survey of the VIMOS field, covering a combined total of ~20 sq. degrees. Given the flux limit of the combined radio catalog (0.1 mJy), we probe a radio luminosity range of 10^36-10^44 erg/s. Using the second and fifth closest neighbor density parameters, we test whether active galaxies inhabit denser environments and study these overdensities in terms of both distance to the AGN and its luminosity. We find evidence for a sub-population of radio-selected AGN that resides in significantly overdense environments at small scales, although we do not find significant overdensities for the bulk of our sample. We do not recover any dependence between the AGN radio-luminosity and overdensities. We show that radio-AGN inhabiting the most underdense environments in the field have vigorous ongoing star formation. We interpret these results in terms of the triggering and fuelling mechanism of radio-AGN.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.447-449
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• 2015

Although the link between activity in the nuclei of galaxy and galactic mergers has been under scrutiny for several years, it is still unclear to what extent and for which populations of active galaxies merger-triggered activity is relevant. The environments of AGN allow an indirect probe of the past merger history and future merger probability of these systems, suffering less from sensitivity issues when extended to higher redshifts than traditional morphological studies of AGN host galaxies. Here we present results from our investigation of the environment of radio selected sources out to a redshift z=2. We employ the first data release J-band catalog of the new near-IR Infrared Medium-Deep Survey (IMS), 1.4 GHz radio data from the Faint Images of the Radio Sky at Twenty-cm (FIRST) survey and a deep dedicated VLA survey of the VIMOS field, covering a combined total of 20 sq. degrees. At a flux limit of the combined radio catalog of 0.1 mJy, we probe over 8 orders of magnitude of radio luminosity. Using the second closest neighbor density parameters, we test whether active galaxies inhabit denser environments. We find evidence for a sub-population of radio-selected AGN that reside in significantly overdense environments at small scales, although we do not find significant overdensities for the bulk of our sample. We show that radio-AGN in the most underdense environments have vigorous ongoing star formation. We interpret these results in terms of the triggering and fuelling mechanism of radio-AGN.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.156-156
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• 2017

Most crop damages have been occurred by vermin(e.g., wild birds and herbivores) during the period between seeding and the cotyledon level. In this study, to minimize the damage by vermin and acquire the benefits such as protection against weeds and maintenance of water content in soil, immediately vinyl mulching after seeding was devised. Vinyl mulching has been generally covered with black color vinyl, that crop seeding locations cannot be detected by visible light range. Before punching vinyl, non-contact and non-destructive methods that can continuously determine the locations are necessary. In this study, a crop position detection method was studied that uses infrared thermal image sensor to determine the cotyledon position under vinyl mulch. The moving system for acquiring image arrays has been developed for continuously detecting crop locations under plastic mulching on the field. A sliding mechanical device was developed to move the sensor, which were arranged in the form of a linear array, perpendicular to the array using a micro-controller integrated with a stepping motor. The experiments were conducted while moving 4.00 cm/s speed of the IR sensor by the rotational speed of the stepping motor based on a digital pulse width modulation signal from the micro-controller. The acquired images were calibrated with the spatial image correlation. The collected data were processed using moving averaging on interpolation to determine the frame where the variance was the smallest in resolution units of 1.02 cm. For this study, the spline method was relatively faster than the other polynomial interpolation methods, because it has a lower maximum order of formulation when using a system such as the tridiagonal linear equation system which provided the capability of real-time processing. The temperature distribution corresponding to the distance between the crops was 10 cm, and the more clearly the leaf pattern of the crop was visually confirmed. The frequency difference was decreased, as the number of overlapped pixels was increased. Also the wave pattern of points where the crops were recognized were reduced.

• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.495-505
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• 2003

Convective weather systems such as organized mesoscale convective systems (Mesoscale Convective Complex, MCC and Convective Cloud Clusters, CCC) and much weaker Disorganized Short-lived Convection (DSC) in the region of India and Nepal were analyzed using the Meteosat-5 IR imagery. The diurnal march and propagation of patterns of convective activity in the Himalayas and Northern Indian subcontinent were examined. Results indicate that infrared satellite images of Northern India and along the southern flank of the Himalayas reveal a strong presence of convective weather systems during the 1999 and 2000 monsoons, especially in the afternoon and during the night. The typical MCCs have life-times of about 11 hours, and areal extent about $300,000km^2$. Although the core of MCC activity remains generally away from the Middle Himalayan range, the occurrence of heavy precipitation events in this region can be directly linked to MCCs that venture into the Lesser Himalayan region and remain within the region bounded by $25^{\circ}-30^{\circ}N$. One principal feature in the spatial organization of convection is the dichotomy between the Tibetan Plateau and the Northern Indian Plains: CCCs and DSCs begin in the Tibetan Plateau in the mid-afternoon into the evening; while they are most active in the mid-night and early morning in the Gangetic Plains and along the southern facing flanks of the Himalayas. Furthermore, these data are consistent with the daily cycle of rainfall documented for a network of 20 hydrometeorological stations in Central Nepal, which show strong nocturnal peaks of intense rainfall consistent with the close presence of Convective Weather Systems (CWSs) in the Gangetic Plains (Barros et al. 2000).

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.4
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• pp.82-92
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• 2006

In the field of image recognition, research on face recognition has recently attracted a lot of attention. The most important step in face recognition is automatic eye detection researched as a prerequisite stage. Existing eye detection methods for focusing on the frontal face can be mainly classified into two categories: active infrared(IR)-based approaches and image-based approaches. This paper proposes an eye region detection method in non-frontal faces. The proposed method is based on the edge--based method that shows the fastest computation time. To extract eye region in non-frontal faces, the method uses edge orientationhistogram of the global region of faces. The problem caused by some noise and unfavorable ambient light is solved by using proportion of width and height for local information and relationship between components for global information in approximately extracted region. In experimental results, the proposed method improved precision rates, as solving 3 problems caused by edge information and achieves a detection accuracy of 83.5% and a computational time of 0.5sec per face image using 300 face images provided by The Weizmann Institute of Science.