• Journal of Sensor Science and Technology
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• v.23 no.3
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• pp.149-157
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• 2014

This paper considers the ability of counting and positioning multi-targets by using a mobile UWB radar device. After a background subtraction process, distinguishing between clutters and human body signals, the position of targets will be computed using weighted Gaussian mixture methods. While computer vision offers many advantages, it has limited performance in poor visibility conditions (e.g., at night, haze, fog or smoke). UWB radar can provide a complementary technology for detecting and tracking humans, particularly in poor visibility or through-wall conditions. As we know, for 2D measurement, one method is the use of at least two receiver antennas. Another method is the use of one mobile radar receiver. This paper tried to investigate the position detection of the stationary human body using the movement of one UWB radar module.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.140-146
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• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.406-410
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• 2005

A depth measurement system that consists of a single camera, a laser light source and a rotating mirror is investigated. The camera and the light source are fixed, facing the rotating mirror. The laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The camera detects the laser light location on object surfaces through the same mirror. The scan over the area to be measured is done by mirror rotation. Advantages are 1) the image of the light stripe remains sharp while that of the background becomes blurred because of the mirror rotation and 2) the only rotating part of this system is the mirror but the mirror angle is not involved in depth computation. This minimizes the imprecision caused by a possible inaccurate angle measurement. The detail arrangement and experimental results are reported.

• Journal of Oral Medicine and Pain
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• v.21 no.1
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• pp.37-54
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• 1996

In this thesis, a new superimposition scheme using a computer vision system was proposed with 7 pairs of skull and ante-mortem photographs, which were already identified through other tests and DNA fingerprints at the Korea National Institute of Scientific Investigation. At this computer vision system, an unidentified skull was caught by video-camcoder with the MPEG and a ante-mortem photograph was scanned by scanner. These two images were processed and superimposed using pixel processing. Recognition of the individual identification by anatomical references was performed on the two superimposed images. These results were as followings. 1. For the enhancement of skull and ante-mortem photographs, various image processing schemes, such as SMOOTH, SHARPEN, EMBOSS, MOSAIC, ENGRAVE, INVERT, NEON and COLOR TO MONO, were applied using 3*5 window processing. As an image processing result of these methods, the optimal techniques were NEON, INVERT and ENGRAVE for the edge detection of skull and ante-mortem photograph. 2. Using various superimposition image processing techniques (SRCOR, SRCAND, SRCINVERT, SRCERASE, DSTINVERT, MERGEPAINT) were compared for the enhancement of image recognition. 3. By means of the video camera, the skull image was inputed directly to a computer system : superimposing it on the ante-mortem photograph made the identification more precise and time-saving. As mentioned above, this image processing techniques for the superimposition of skull and ante-mortem photographs simply used the previous approach, In other wrods, taking skull photographs and developing it to the same size as the ante-mortem photographs. This system using various image processing techniques on computer screen, a more precise and time-saving superimposition technique could be able to be applied in the area of individual identification in forensic practice.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.342-351
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• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.793-797
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• 2003

In this paper, we present a self-localization method for mobile robots using vertical line features of indoor environment. When a 2D map including feature points and color information is given, a mobile robot moves to the destination, and acquires images by one camera from the surroundings having vertical line edges. From the image, vertical line edges are detected, and pattern vectors meaning averaged color values of the left and right region of each line segment are computed. The pattern vectors are matched with the feature points of the map using the color information and the geometrical relationship of the points. From the perspective transformation of the corresponded points, nonlinear equations are derived. Localization is carried out from solving the equations by using Newton's method. Experimental results show that the proposed method using mono view is simple and applicable to indoor environment.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.62-66
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• 2000

This study investigated the effects of certain specific wavelengths of lighting on the autonomic nervous system (ANS) using the heart rate variability (HRV) as an index. Six subjects with normal color vision participated n this study between 15:00 and 17:00 hr to neutralize any visual differences arising from circadian rhythm. The environmental conditions of the laboratory were maintained in complete darkness and the temperature was equilibrated at 24$\Box$ with a relative humidity of 60%. Subjects were only subjected to light stimulation when the pupil of dyes attained a minimum size of 2 mm by projecting illumination equalized with the same spectral radiance of 500-700 nm with 50-nm internal radiance. HRV was calculated from electrocardiogram (ECG) with systematic respiratory control at 0.35 Hz. The results suggest that illumination with certain wavelengths may induce ANS activation.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.485-488
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• 2002

In this paper, fuzzy logic controllers are designed for compensation of distance errors. Because we can't know information of the depth in a mono camera, these errors are occurred. Also, they are increased as a target object is to keep away from a center of image. Therefore, the errors for each position of joints of an arm robot should be modeled, but accurate models can't be obtained because of no information of the depth, uncertain feature points of image, parameter uncertainties, and illumination. Hence, fuzzy logic controllers for each error are designed for compensation. This paper consists of color image processing, error modeling, and the controller design. Experimental results are given to verify the effectiveness of our proposed method.

• The International Journal of Costume Culture
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• v.4 no.1
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• pp.9-17
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• 2001

The purposes of the study are to find out the effect of clothing colors on perception of stimulus ages, occupations and images using stereotyping and color vision theories. The research method is a qualitative study and materials developed for the study are a set of stimuli and open-ended responses. The subjects were 1138 undergraduate students in Taejoen city, Chungbuk province. The data is analyze using content analysis, supplementary frequency and χ²analysis. The results are as follows : 1) The colors in Korean traditional costumes affected on the wearer's age perception : The red ensemble give the wearer the youngest look while the gray give the oldest look. 2) Mono-color ensemble wearers tend to give older look than bi-color ensemble wearers. 3) The chima colors and the jogori colors have similar impact on the wearer's age perception. 4) On image perception the jogori colors have more impact than the chima colors. 5) The colors in Korean traditional costumes are the clues to estimate the wearer's occupation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.346-352
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• 2011

This paper presents a system of road extraction for traffic images from a single camera. The road in the images is subject to large changes in appearance because of environmental effects. The proposed system is based on the integration of color correlograms and random forest. The color correlogram depicts the color properties of an image properly. Using the random forest, road extraction is formulated as a learning paradigm. The combined effects of color correlograms and random forest create a robust system capable of extracting the road in very changeable situations.