• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.63-73
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• 2007

This paper proposes an illuminant-adaptive reproduction method using light adaptation and flare conditions for a mobile display. Displayed images in daylight are perceived as quite dark due to the light adaptation of the human visual system, as the luminance of a mobile display is considerably lower than that of an outdoor environment. In addition, flare phenomena decrease the color gamut of a mobile display and de-saturating the chroma. Therefore, this paper presents an enhancement method composed of lightness enhancement and chroma compensation. First, the ambient light intensity is measured using a lux-sensor, then the flare is calculated based on the reflection ratio of the display device and the ambient light intensity. To improve the perceived image, the image's luminance is transformed by linearization of the response to the input luminance according to the ambient light intensity. Next, the displayed image is compensated according to the physically reduced chroma, resulting from flare phenomena. This study presents a color reproduction method based on an inverse cone response curve and flare condition. Consequently, the proposed algorithm improves the quality of the perceived image adaptive to an outdoor environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.624-631
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• 2008

This paper presents a method for a mobile robot to follow a moving object in real time. The robot follows a target object keeping the facing angle toward the target and the distance to the target to given value. The method consists of two procedures: first, the detection of target position in the robot coordinate system, and the second, the calculation of translational velocity and rotational velocity to follow the object:. To detect the target location, range sensor data is represented in histogram. Based on the real time calculation of the location of the target relative to the robot, translational velocity and rotational velocity to follow the target are calculated. The velocities make the heading angle and the distance to target converge toward the desired ones. The performance of the method is tested through simulation. In the simulation, the target moves with three different trajectories, straight line trajectory, rectangular trajectory, and circular trajectory. As shown in the results, it is inevitable to lose track temporarily of the target when the target suddenly changes its motion direction. Nevertheless, the robot speeds up to catch up and finally succeeds to follow the target as soon as possible even in this case. The proposed method can also be utilized to coordinate the motion of multiple robots to keep their formation as well as to follow a target.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.82.2-82.2
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• 2013

The NISS (Near-infrared Imaging Spectrometer for Star formation history) onboard NEXTSat-1 is being developed by KASI. The NISS will perform the imaging low-resolution spectroscopic observation in the near-infrared range for nearby galaxies, low background regions, starforming regions and so on. The off-axis reflecting telescope with a wide field of view (2 deg. ${\times}$ 2 deg.) will be operated in the wavelength range from 0.95 to $3.8{\mu}m$. In order to reduce thermal noise, a telescope and a HgCdTe infrared sensor will be cooled down to 200K and 80K, respectively. To evade a stray light outside a field of view and use limited space efficiently, the NISS adopted the off-axis reflective optical system. The primary and secondary mirrors, optomechanical part and mechanical structure were designed to use the same material. It will lessen the degradation of optical performance due to a thermal variation. The purpose of NISS is the observation of cosmic near-infrared background in the wide wavelength range as well as the detection of near-infrared spectral lines in nearby galaxies, cluster of galaxies and star forming regions. It will give us less biased information on the star formation history. In addition, we will demonstrate the space technologies related to the development of the Korea's leading near-infrared instrument for the future large infrared telescope, SPICA.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.35-45
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• 2016

Melatonin hormone involved in human's circadian rhythm adjustment sensitively responds to light's specific short wavelength ratio. A shift worker's circadian rhythm disturbance and sleep disorder are caused by the existing lighting conditions, whose short wavelength ratio is fixed. The life pattern of a shift worker changes irregularly because of irregular working hours and the same lighting environment; thus, his/her concentration is reduced. For such a reason, negative effects ensue to the detriment of healthy everyday life, including a high risk of accidents or having unsound sleep after leaving work. A smartphone-based wavelength control LED lighting system that targets shift workers and that can easily measure and control lighting suitable for wake-sleep cycle, according to working hours and closing hours, is proposed in this paper. First, after the light characteristics of LED lighting that changes depending on light control ratio are measured through the color sensor installed on the smartphone and the externally-linked Mini-Spectrometer, they are stored in the database. Based on the stored optical characteristics data, the measurement module and light control module are implemented. Lighting is offered using a control ratio having the maximum rate of short wavelength in consideration of the target illuminance, classified according to work type by identifying working hours as time when waking is required for shift workers. After a shift work leaves work, the amount of lighting is varied, using a control ratio having a minimum short wavelength rate so that a shift worker can enter the sleep state naturally.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.133-144
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• 2020

The number of elderly people with dementia is increasing as fast as the proportion of older people due to aging, which creates a social and economic burden. In particular, dementia care costs, including indirect costs such as increased care costs due to lost caregiver hours and caregivers, have grown exponentially over the years. In order to reduce these costs, it is urgent to introduce a management system to care for dementia patients. Therefore, this study proposes a sensor-based abnormal behavior detection system to manage dementia patients who live alone or in an environment where they cannot always take care of dementia patients. Existing studies were merely evaluating behavior or evaluating normal behavior, and there were studies that perceived behavior by processing images, not data from sensors. In this study, we recognized the limitation of real data collection and used both the auto-encoder, the unsupervised learning model, and the LSTM, the supervised learning model. Autoencoder, an unsupervised learning model, trained normal behavioral data to learn patterns for normal behavior, and LSTM further refined classification by learning behaviors that could be perceived by sensors. The test results show that each model has about 96% and 98% accuracy and is designed to pass the LSTM model when the autoencoder outlier has more than 3%. The system is expected to effectively manage the elderly and dementia patients who live alone and reduce the cost of caring.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1003-1017
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• 2017

Multispectral image data of high spatial resolution is required to obtain correct information on the ground surface. The multispectral image data has lower resolution compared to panchromatic data. PAN-sharpening fusion technique produces the multispectral data with higher resolution of panchromatic image. Recently the object-based approach is more applied to the high spatial resolution data than the conventional pixel-based one. For the object-based image analysis, it is necessary to perform image segmentation that produces the objects of pixel group. Image segmentation can be effectively achieved by the process merging step-by-step two neighboring regions in RAG (Regional Adjacency Graph). In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. This degradation increases variation of pixel values in same area, and results in deteriorating the accuracy of image segmentation. An iterative approach that reduces the difference of pixel values in two neighboring pixels of same area is employed to alleviate variation of pixel values in same area. The size of segmented regions is associated with the quality of image segmentation and is decided by a stopping rue in the merging process. In this study, the image restoration and segmentation was quantitatively evaluated using simulation data and was also applied to the three PAN-sharpened multispectral images of high resolution: Dubaisat-2 data of 1m panchromatic resolution from LA, USA and KOMPSAT3 data of 0.7m panchromatic resolution from Daejeon and Chungcheongnam-do in the Korean peninsula. The experimental results imply that the proposed method can improve analytical accuracy in the application of remote sensing high resolution PAN-sharpened multispectral imagery.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1209-1220
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• 2020

In the case of forest areas, the installation of ground control points (GCPs) and the selection of terrain features, which are one of the unmanned aerial photogrammetry work process, are limited compared to urban areas, and safety problems arise due to non-visible flight due to high forest. To compensate for this problem, the drone equipped with a real time kinematic (RTK) sensor that corrects the position of the drone in real time, and a 3D flight method that fly based on terrain information are being developed. This study suggests to present a method for investigating damage using drones in forest areas. Position accuracy evaluation was performed for three methods: 1) drone mapping through GCP measurement (normal mapping), 2) drone mapping based on topographic data (3D flight mapping), 3) drone mapping using RTK drone (RTK mapping), and all showed an accuracy within 2 cm in the horizontal and within 13 cm in the vertical position. After evaluating the position accuracy, the volume of the landslide area was calculated and the volume values were compared, and all showed similar values. Through this study, the possibility of utilizing 3D flight mapping and RTK mapping in forest areas was confirmed. In the future, it is expected that more effective damage investigations can be conducted if the three methods are appropriately used according to the conditions of area of the disaster.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.197-208
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• 2007

Enormously sized buildings are appearing world-wide with the advancement of construction techniques. Large-scaled and complicated structures will have increased difficulties for dealing with safety, and will demand well-matched safety measures. This research introduced up-to-date techniques and systems which are applied in buildings in foreign nations. Furthermore, it proposed s direct guidance plan for buildings in case of fire. Since it is possible to install wireless sensor networks which detect fires or effects of fire, the plan makes use of this information. Accordingly, the authors completed a direct guidance plan that was based on omnidirectional guidance lights. It is possible to select a route with concern about both time and capacity with a concept of a non-dominated path. Finally, case studies showed that quickest path algorithms were effective for guiding efficient dispersion routes and in case of restriction of certain links in preferred paths due to temperature and smoke, it was possible to avoid relevant links and to restrict demand in the network application. Consequently, the algorithms were able to maximize safety and minimize evacuation time, which were the purposes of this study.