• Journal of the Korean Magnetic Resonance Society
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• v.8 no.2
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• pp.108-114
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• 2004

Recently a new method for magnetic resonance imaging based on the detection of relatively strong signal from intermolecular multiple quantum coherences (iMQCs) is reported. Such a signal would not be observable in the conventional framework of magnetic resonance; it originates in long-range dipolar couplings that are traditionally ignored. In this paper, we present the results of experimental studies to assess the feasibility of intermolecular double quantum coherences (iDQCs) imaging in humans. We show that the iDQC images are readily observable at 4T and that they do indeed provide different contrast than appears in conventional images.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.4
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• pp.270-274
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• 2006

A color filter array (CFA) helps a single electrical image sensor to recognize color images. The Red-Green-Blue (RGB) Bayer CFA is commonly used, but the amount of the light which arrives at the photodiode is attenuated with this CFA. Red-White-Blue (RWB) CFA increases the amount of the light which arrives at photodiode by using White (W) pixels instead of Green (G) pixels. However, white pixels are saturated earlier than red and blue pixels. The pseudo multiple capture scheme and the corresponding RWB CFA were proposed to overcome the early saturation problem of W pixels. The prototype CMOS image sensor (CIS) was fabricated with $0.35-{\mu}m$ CMOS process. The proposed CIS solves the early saturation problem of W pixels and increases the dynamic range.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.257-264
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• 2009

This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a mobile robot. The proposed approach can locate extremely small-sized face regions of $12{\times}12$ pixels. We solve a tiny face detection problem by organizing a system that consists of multiple detectors including a mean-shift color tracker, short- and long-rage face detectors, and an omega shape detector. The proposed method adopts the long-range face detector that is well trained enough to detect tiny faces at a long range, and limiting its operation to only within a search region that is automatically determined by the mean-shift color tracker and the omega shape detector. By focusing on limiting the face search region as much as possible, the proposed method can accurately detect tiny faces at a long distance even with a low-resolution image, and decrease false positives sharply. According to the experimental results on realistic databases, the performance of the proposed approach is at a sufficiently practical level for various robot applications such as face recognition of non-cooperative users, human-following, and gesture recognition for long-range interaction.

• Journal of electromagnetic engineering and science
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• v.19 no.1
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• pp.13-19
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• 2019

This paper proposes a systematic method for estimating detection performances of a frequency-modulated continuous wave radar using electromagnetic simulations. The proposed systematic method includes a radar system simulator that can obtain range-Doppler images using the electromagnetic (EM) simulations in conjunction with a test setup employed for performance evaluation of multiple targets at different velocities in a traffic environment. This method is then applied for optimizing the half-power beamwidths of the antenna array using an evaluation metric defined to improve the detection strengths for the multiple targets. The optimized antenna has vertical and horizontal half-power beam widths of $10^{\circ}$ and $60^{\circ}$, respectively. The results confirm that that the proposed systematic method is suitable to improve the radar detection performance with the enhanced radar-Doppler images.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.46-52
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• 1998

This paper presents an experimenal proof for criteria of selecting an optimum adaptive beamforming (ABF) algorithm for a large distorted phased array. A single point target embedded in clutter model is suggested to compare four well-known ABF algorithms. These algorithms are tested to low variance and high variance real data for self-calibrating a large distored phased array. It is shown that these algorithms require at least one dominant scatterer with large radar cross section (RCS) or multiple scatterers with moderate RCS in the field of view. Experimental results are provided to demonstrate the comparisons of the four algorithems in terms of gain loss and image correlaion coefficient, along with corresponding reconstructed cross-range images and range-azimuth images.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.6-41
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• 2001

As autonomous mobile robot become more widely used in industry, the importance of navigation system is rising, But eh primary method of locomotion is with wheels, which cause man problems in controlling tracked mobile robots. In this paper, we discuss the used navigation control of tracked mobile robots with multiple sensors. The multiple sensors are composed of ultrasonic wave sensors and vision sensors. Vision sensors gauge distance using a laser and create visual images, to estimate robot position. The 80196 is used at close range and the vision board is used at long range. Data is managed in the main PC and management is distributed to ever sensor. The controller employs fuzzy logic.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.105-115
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• 2005

An environment model that is constructed using a single image has the problem of a blurring effect caused by the fixed resolution, and the stretching effect of the 3D model caused when information that does not exist on the image occurs due to the occlusion. This paper introduces the registration and integration method using multiple images to resolve the above problem. This method can represent parallax effect and expand the environment model to represent wide range of environment. The segmentation-based environment modeling method using multiple images can build a detail model with optimal resolution.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.120-127
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• 2000

Adaptive template filtering has been proposed recently for enhancement of signal-to-noise ratio without loss of resolution. In the adaptive template filtering, an optimal template among multiple templates is selected, then linear least square error filtering based on the template is applied in vowel by vowel basis. In some magnetic resonance imaging, where the distribution of gray level has relatively small dynamic range, e.g., $T_1$ imaging, however, artificial stair-like artifact is observed at near edges. This is partially due to the edge enhancement effect in such yokels that contain multiple compounds at the boundaries of tissues. The gray levels of these yokels become similar gray levels of near dominant vowels that contain single compound by the adaptive filtering, which enlarges edge discontinuities. In this paper, we propose a technique to eliminate such artifact by identifying those yokels that contain multiple compounds and assigning the largest template for them. Filtered images with the proposed technique show substantial visual enhancement at the edges without degradation of peak signal-to-noise ratio compared to the original adaptive template filtering for both magnetic resonance images and phantom images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1231-1236
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• 2006

The contrast control of images with narrow dynamic range is a simple method among enhancement methods for low intensity of image. Histogram equalization is the most common method for this purpose, which stretches the dynamic range of intensity Conventional methods would fail to enhance images with extremely dark and bright regions, because of not considering the shape of histogram. In this paper, we propose a novel adaptive histogram equalization based on histogram matching with multiple Gaussian transformation function. As a result, output images with a couple of peaks of histogram could be improved and the details such as edges in dark regions could be appeared better than conventional method subjectively.

• The Research Journal of the Costume Culture
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• v.22 no.3
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• pp.399-410
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• 2014

The purpose of this study was to investigate emotional images and preference of knitwear by tone on tone combination. The subjects were 357 university students in Daejeon and Chungnam province, and the measuring instruments were 6 stimuli manipulated by color and tone combination type of background and pattern in the tone and tone combination, and self-administrated questionnaires consisted of emotional images items, preference items, and subjects' demographics attributions. The data were analyzed by Cronbach's ${\alpha}$, factor analysis, t-test, MANOVA and Duncan's multiple range test, using SPSS program. The results were as follows. First, four factors (attractiveness, conspicuity, mildness, and activity) are emerged on emotional images of knitwear. Second, color had main effects on emotional images and preference. Gray color was perceived as most attractive image and more preferred than others. Third, tone combination type had some effects on emotional images. Vivid tone background/light tone pattern was perceived more attractive image but less conspicuous and mild than light tone background/vivid tone pattern. Forth, subjects' gender had an effects on conspicuous image. Male was perceived more conspicuous image on knitwear stimuli than female. Fifth, color and subjects' gender had interaction effects on attractiveness image and preference. Male perceived that blue is more attractive and preferred than female.