• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1535-1541
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• 2019

To carry out safe and rapid decontamination in radiological accident areas, acquisition of various information on radiation sources is needed. In particular, to figure out the location and distribution of radiation sources is essential for rapid follow-up and removal of contaminants as well as minimizing worker damage. The radiation distribution detection device is used to obtain the position and distribution information of the radiation source. In the case of a radiation distribution detection device, a detection sensor unit is generally composed of a single sensor, and the detection range is limited due to the physical characteristics of the single sensor. We applied a calibration detector for controlling the detection sensitivity of a single sensor for radiation detection and improved the limited detection range of radiation dose rate. Also, gamma irradiation test confirmed the improvement of radiation distribution detection range.

• Smart Structures and Systems
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• v.28 no.6
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• pp.779-789
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• 2021

Cracks in railway sleeper are an inevitable condition and has a significant influence on the safety of railway system. Although the technology of railway sleeper condition monitoring using machine learning (ML) models has been widely applied, the crack recognition accuracy is still in need of improvement. In this paper, a two-stage method using edge detection and convolutional neural network (CNN) is proposed to reduce the burden of computing for detecting cracks in railway sleepers with high accuracy. In the first stage, the edge detection is carried out by using the 3×3 neighborhood range algorithm to find out the possible crack areas, and a series of mathematical morphology operations are further used to eliminate the influence of noise targets to the edge detection results. In the second stage, a CNN model is employed to classify the results of edge detection. Through the analysis of abundant images of sleepers with cracks, it is proved that the cracks detected by the neighborhood range algorithm are superior to those detected by Sobel and Canny algorithms, which can be classified by proposed CNN model with high accuracy.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.1
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• pp.54-63
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• 2005

Detection ranges of acoustic instruments mainly used for fisheries and their research are derived as the range bordered by a certain signal-to-noise ration (SNR) thershold. The SNR is depicted by several factors on transmitting and receiving, sound propagation, scattering by objects, and mainly self-ship noise. The detection ranges are shown for several fisheries instrument, such as echo sounder, quantiative echo sounder, and bio-telemetry system. The results can be used for designing the instruments, examining the capability of user's own instruments, and interpreting obtained data or echograms. Increasing transmitting power is not as effective for high frequencies as for low frequencies to increase the detection range. Comparison of volume backscattering strengths obtained by the quantitative echo sounder at several frequencies should be done within the same detection range. By applying the concept of the detection range for the bio-telemetry receiver beams, the number of the beams and the beamwidths can be determined.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1
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• pp.47-56
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• 2008

In the detection of an underwater target, there exists an optimal search depth for the sonar systems, at which the Probability of Detection is maximized. The optimal search depth is dependent on the depths of the target and sonar, the sound speed profile, and the bathymetry. In this paper, we address this question in range-dependent environments, particularly for the bathymetry with slope and with warm eddy. For range-dependent bathymetry, the typical sound profile in the East Sea of Korea was used. The detection range was greater when the sonar was located in deep water than in shallow water. As for the case of eddy, mesoscale warm eddy was used, and the detection range was greater when looking out of the warm eddy than when looking into the eddy.

• 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 Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.62-68
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• 2012

In this paper, a detection method of a pedestrian safety road marking was proposed. The proposed algorithm uses laser range and reflectivity of a range finder (LRF). For a detection of crosswalk marking and stop line, the DFT (Discrete Fourier Transform) of reflectivity and cross-correlation method between the reference replica and the measured reflectivity are used. A speed bump is detected through measuring an altitude difference of two LRFs which have the different tilted angle. Furthermore, we proposed a velocity constrained a detection method of a speed bump. Finally, the proposed methods are tested in on-line, on the pavement of a road. The considered road markings are wholly detected. The localization errors of both road markings are smaller than 0.4 meter.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.22 no.4
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• pp.98-103
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• 1986

The passive acoustic system only has generally used in fish detection. But the passive acoustic system has not been tried in fishing since Freytag has proposed a possibilities of the passive detection of fishes in 1963. This paper describes the .feasible aspects of fish detection by listening of the sound they make. The passive acoustic system accompanied the active acoustic system may expand the range of detection and compensate for lack of capabilities each other, but there are some difficulties in noise rejection because the fre9uency range of ship noises covers the whole range vf biological sounds. The attempt to collect useful informations from underwater would be greatly contributed in fisheries.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.857-860
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• 2005

Several algorithms have been developed for the data processing of spotlight synthetic aperture radar (SAR). In particular, the range migration algorithm (RMA) does not assume that illuminating wavefronts are planar. Also, a high resolution image can be obtained by the RMA. This paper introduces an extension of the original RMA to enable a more efficient airborne SAR data processing. We consider more general motion and scene than the original RMA. The presented formulation is analyzed by using the principle of the stationary phase. Finally, the extended algorithm is tested with numerical simulations using the pulsed spotlight SAR.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.89-95
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• 2015

In this paper, we propose a real-time two-dimensional bar code detection system even at long range using a vision technique. We first perform short-range detection, and then long-range detection if the short-range detection is not successful. First, edge map generation, image binarization, and connect component labeling (CCL) are performed in order to select a region of interest (ROI). After interpolating the selected ROI using bilinear interpolation, a location symbol pattern is detected as the same as for short-range detection. Finally, the symbol pattern is arranged by applying inverse perspective transformation to localize bar codes. Experimental results demonstrate that the proposed system successfully detects bar codes at two or three times longer distance than existing ones even at indoor environment.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.6
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• pp.706-711
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• 2014

A low power 6-bit flash ADC that uses an input voltage range detection algorithm is described. An input voltage level detector circuit has been designed to overcome the disadvantages of the flash ADC which consume most of the dynamic power dissipation due to comparators array. In this work, four digital input voltage range detectors are employed and each input voltage range detector generates the specific clock signal only if the input voltage falls between two adjacent reference voltages applied to the detector. The specific clock signal generated by the detector is applied to turn the corresponding latched comparators on and the rest of the comparators off. This ADC consumes 68.82 mW with a single power supply of 1.2V and achieves 4.3 effective number of bits for input frequency up to 1 MHz at 500 MS/s. Therefore it results in 4.6 pJ/step of Figure of Merit (FoM). The chip is fabricated in 0.13-um CMOS process.