• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.255-264
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• 2011

In this paper, we propose a forward vehicle detection algorithm using column detection and bird's-eye view mapping based on stereo vision. The algorithm can detect forward vehicles robustly in real complex traffic situations. The algorithm consists of the three steps, namely road feature-based column detection, bird's-eye view mapping-based obstacle segmentation, obstacle area remerging and vehicle verification. First, we extract a road feature using maximum frequent values in v-disparity map. And we perform a column detection using the road feature as a new criterion. The road feature is more appropriate criterion than the median value because it is not affected by a road traffic situation, for example the changing of obstacle size or the number of obstacles. But there are still multiple obstacles in the obstacle areas. Thus, we perform a bird's-eye view mapping-based obstacle segmentation to divide obstacle accurately. We can segment obstacle easily because a bird's-eye view mapping can represent the position of obstacle on planar plane using depth map and camera information. Additionally, we perform obstacle area remerging processing because a segmented obstacle area may be same obstacle. Finally, we verify the obstacles whether those are vehicles or not using a depth map and gray image. We conduct experiments to prove the vehicle detection performance by applying our algorithm to real complex traffic situations.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.2
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• pp.192-197
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• 2012

In this paper, a non-contact microwave technique was presented to detect the surface crack of the metals. An open-ended coaxial cable line was used as a sensor at 11 GHz, and the reflection coefficients were measured by scanning along the metal surface including artificial surface cracks. A parameter, the K value which was defined as the difference between maximum and minimum reflection coefficients, was measured and used to estimate the crack depth. A linear relationship between the K value and crack depth was found. This study showed that non-contact detection of the surface cracks of metals is possible using the open-ended coaxial line sensor at X-band.

• Journal of Ocean Engineering and Technology
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• v.27 no.3
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• pp.61-66
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• 2013

This paper presents the results of finite element simulations of elastic wave propagation in an underwater steel plate and the verification of a proposed method utilizing elastic wave-based damage detection. For the simulation and verification, we carried out the following procedures. First, three-dimensional finite element models were constructed using a general purpose finite element program. Second, two types of damages (mechanical defects and deteriorations) were applied to the underwater steel plate and three parameters (defect location, defect width, and depth) were considered to adjust the severity of the applied damages. Third, elastic waves were generated using the oblique incident method with a Gaussian tone burst, and the response signals were obtained at the receiving point for each defect or deterioration case. In addition, the received time domain signals were analyzed, particularly by measuring the magnitudes of the maximum amplitudes. Finally, the presence and severity of each type of damage were identified by the decreasing ratios of the maximum amplitudes. The results showed that the received signals for the models had the same global pattern with minor changes in the amplitudes and phases, and the decreasing ratio generally increased as the damage area increased. In addition, we found that the defect depth was more critical than the width in the decrease of the amplitude. This mainly occurred because the layout of the depth interfered with the elastic wave propagation in a more severe manner than the layout of the width. An inverse analysis showed that the proposed method is applicable for detecting mechanical defects and quantifying their severity.

• The Journal of Korean Physical Therapy
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• v.14 no.4
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• pp.119-130
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• 2002

The purpose of this study was to evaluate hemodynamics of intracranial blood flow for obtain clinically useful reference values and assess cerebral hemodynamics change with aging. 81 normal Korean subjects(age, 14$\thicksim\∼\thicksim$70 years) examined who han no history of neurologic disease and the subjects divided into group A(age, 14$\∼$39 years), group B(age, 40$\∼$59 years) and group C(age, 60$\∼$70 years). Transcranial doppler was use for measured the maximum velocity(Vmax), mean velocity(Vmean), pulsatility index(PI), resistive index(RI), stenosis index(SI) and depth of sample volume. Vmax was 99.1 1cm/s, Vmean was 63.57cm/s, PI was 0.85, RI was 0.56, SI was 31.94 and depth of sample volume was 52.35 in middle cerebral artery. Vmax was 85.54cm/s, Vmean was 52.52cm/s, PI was 0.82, RI was 0.55, SI was 34.48 and depth of sample volume was 73.62 in anterior cerebral artery. Vmax was 75.45cm/s, Vmean was 45.60cm/s, PI was 0.82, RI was 0.58, SI was 36.14 and depth of sample volume was 62.35 in posterior cerebral artery. Vmax was 70.44cm/s, Vmean was 47.07cm/s, PI was 0.87, RI was 0.58, SI was 29.83 and depth of sample volume was 75.23 in basilar artery Vmax was 63.92, Vmean was 42.42, PI was 0.89, RI was 0.58, SI was 29.89 and depth of sample volume was 66.65 in vertebral artery. Vmax and Vmean was significantly decreased with increasing age in middle cerebral artery, anterior cerebral artery, posterior cerebral artery, basilar artery and vertebral artery And PI and RI was significantly increased with increasing age in basilar artery and vertebral artery. And I suggest that transcranial doppler sonography can be used as one of useful clinical tool for detection of cerebral hemodynamics.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.3
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• pp.9-18
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• 2001

In this paper, we present the joint symbol detection and channel estimation for an orthogonal frequency division multiplexing (OFDM) system in fading channels. The proposed methods are based on decision-directed channel estimation (DDCE) method and their symbol detection is achieved by using Viterbi algorithm. This Viterbi decision-directed channel estimation (VDDCE) method tracks time-varying channels and detects a maximum likelihood symbol sequence. Recursive Viterbi decision-directed channel estimation (RVDDCE) method based on VDDCE method is proposed to shorten the detecting depth. In this method, channel estimate and Viterbi processing are recursively performed every interval of training symbol. Also, average chann'el estimation (ACE) technique to reduce the effect of additive white Gaussian noise (AWGN) is applied VDDCE method and RVDDCE method. These proposed methods arc demonstrated by computer simulation.

• Journal of Magnetics
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• v.20 no.3
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• pp.312-316
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• 2015

Unlike conventional Eddy Current Test (ECT), Pulsed Eddy Current (PEC) uses a multiple-frequency current pulse through the excitation coil. In the present study, the detection of subsurface cracks using a specially designed probe that allows the detection of a deeper crack with a relatively small current density has been attempted using the PEC technique. The tested sample is a piece of 304 stainless steel (SS304) with a thickness of 30mm. Small electrical discharge machining (EDM) notches were put in the test sample at different depths from the surface to simulate the subsurface cracks in a pipe. The designed PEC probe consists of an excitation coil and a Hall sensor and can detect a subsurface crack as narrow and shallow as 0.2 mm wide and 2 mm deep. The maximum distance between the probe and the defect is 28 mm. The peak amplitude of the detected pulse is used to evaluate the cracks under the sample surface. In time domain analysis, the greater the crack depth the greater the peak amplitude of the detected pulse. The experimental results indicated that the proposed system has the potential to detect the subsurface cracks in stainless steel plates.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.179-180
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• 1998

In this paper, we propose an algorithm to detect fetal movements using M-mode ultrasonography. To do this work automatically, we find the crosscorrelation between the current data vector of the depth direction of M-mode image and the previous one. In the crosscorrelation estimator, the variations of time lag $\tau$ at maximum crosscorrelation value means fetal movements. A woman in the 37th week of pregnancy was monitored and the ultrasonic image of fetus was recorded over 20-minute period to detect fetal movements using B-mode and M-mode ultrasonography simultaneously. And the presented method was compared with maternal perception and B-mode ultrasonography observed by clinician. The maternal perception method detected only 57% of all fetal movements observed by clinician. The detection of the presented method corresponds to the clinician's detection result.

• International Journal of Highway Engineering
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• v.18 no.2
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• pp.37-42
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• 2016

PURPOSES : The objective of this study is to determine the optimal frequency of ground penetrating radar (GPR) testing for detecting the voids under the pavement. METHODS : In order to determine the optimal frequency of GPR testing for void detection, a full-scale test section was constructed to simulate the actual size of voids under the pavement. Voids of various sizes were created by inserting styrofoam at varying depths under the pavement. Subsequently, 250-, 500-, and 800-MHz ground-coupled GPR testing was conducted in the test section and the resulting GPR signals were recorded. The change in the amplitude of these signals was evaluated by varying the GPR frequency, void size, and void depth. The optimum frequency was determined from the amplitude of the signals. RESULTS: The capacity of GPR to detect voids under the pavement was evaluated by using three different ground-coupled GPR frequencies. In the case of the B-scan GPR data, a parabolic shape occurred in the vicinity of the voids. The maximum GPR amplitude in the A-scan data was used to quantitatively determine the void-detection capacity. CONCLUSIONS: The 250-MHz GPR testing enabled the detection of 10 out of 12 simulated voids, whereas the 500-MHz testing allowed the detection of only five. Furthermore, the amplitude of GPR detection associated with 250-MHz testing is significantly higher than that of 500-MHz testing. This indicates that 250-MHz GPR testing is well-suited for the detection of voids located at depths ranging from 0.5~2.0 m. Testing at frequencies lower than 250 MHz is recommended for void detection at depths greater than 2 m.

• Fisheries and Aquatic Sciences
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• v.14 no.3
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• pp.218-225
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• 2011

Dual frequency identification sonar (DIDSON) is an imaging sonar that has been used for numerous fisheries investigations in a diverse range of freshwater and marine environments. The main purpose of DIDSON is fish counting, fish sizing, and fish behavioral studies. DIDSON records video-quality data, so processing power for handling the vast amount of data with high speed is a priority. Therefore, a semiautomated analysis of DIDSON data for fish counting, sizing, and fish behavior in Echoview (fisheries acoustic data analysis software) was accomplished using testing data collected on the Rakaia River, New Zealand. Using this data, the methods and algorithms for background noise subtraction, image smoothing, target (fish) detection, and conversion to single targets were precisely illustrated. Verification by visualization identified the resulting targets. As a result, not only fish counts but also fish sizing information such as length, thickness, perimeter, compactness, and orientation were obtained. The alpha-beta fish tracking algorithm was employed to extract the speed, change in depth, and the distributed depth relating to fish behavior. Tail-beat pattern was depicted using the maximum intensity of all beams. This methodology can be used as a template and applied to data from BlueView two-dimensional imaging sonar.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1967-1972
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• 2016

This paper defines a distance graph for a hand region in a depth image and proposes an algorithm detecting finger using it. The distance graph is a graph expressing the hand contour with angles and Euclidean distances between the center of palm and the hand contour. Since the distance graph has local maximum at fingertips' position, we can detect finger points and recognize the number of them. The hand contours are always divided into 360 angles and the angles are aligned with the center of the wrist as a starting point. And then the proposed algorithm can well detect fingers without influence of the size and orientation of the hand. Under some limited recognition test conditions, the recognition test's results show that the recognition rate is 100% under 1~3 fingers and 98% under 4~5 fingers and that the failure case can also be recognized by simple conditions to be available to add.