• Journal of Advanced Navigation Technology
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• v.16 no.5
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• pp.846-852
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• 2012

The result of imaging segmentation becomes different with the parameters involved in the segmentation algorithms; therefore, the parameters for the optimal segmentation have been found through a try and error. In this paper, we propose the method to find the best values of parameters involved in the area-based active contour method using three-way ANOVA. The segmentation result applied by three-way ANOVA is compared with the optimal segmentation which is drawn by user. We use the global consistency rate for comparing two segmentations. Finally, we estimate the main effects and interactions between each parameter using three-way ANOVA, and then calculate the point and interval estimate to find the best values of three parameters. The proposed method will be a great help to find the optimal parameters before working the motion segmentation using piecewise constant model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1759-1771
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• 1994

We proposed the iterative image restoration method based on the method of steepest descent with a regularization constraint for restoring the noisy motion-blurred images. The conventional method proposed by Jan Biemond et al, had drawback to amplify the additive noise and make ringing effects in the restored images by determining the value of regularization parameter experimentally from the degraded image to be restored without considering local information of the restored one. The method we proposed had a merit to suppress the noise amplification and restoration error by using the regularization parameter which estimate the value of it adaptively from each pixels of the image being restored in order to reduce the noise amplification and ringing effects efficiently. Also we proposed the termination rule to stop the iteration automatically when restored results approach into or diverse from the original solution in satisfaction. Through the experiments, proposed method showed better result not only in a MSE of 196 and 453 but also in the suppression of the noise amplification in the flat region compared with those proposed by Jan Biemond et al. of which MSE of 216 and 467 respectively when we used 'Lean' and 'Jaguar' images as original images.

• Radiation Oncology Journal
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• v.35 no.1
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• pp.65-70
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• 2017

Purpose: To evaluate the utility of implanted surgical clips for detecting interfractional errors in the treatment of hepatobiliary and pancreatic cancer with postoperative radiotherapy (PORT). Methods and Materials: Twenty patients had been treated with PORT for locally advanced hepatobiliary or pancreatic cancer, from November 2014 to April 2016. Patients underwent computed tomography simulation and were treated in expiratory breathing phase. During treatment, orthogonal kilovoltage (kV) imaging was taken twice a week, and isocenter shifts were made to match bony anatomy. The difference in position of clips between kV images and digitally reconstructed radiographs was determined. Clips were consist of 3 proximal clips (clip_p, ${\leq}2cm$) and 3 distal clips (clip_d, >2 cm), which were classified according to distance from treatment center. The interfractional displacements of clips were measured in the superior-inferior (SI), anterior-posterior (AP), and right-left (RL) directions. Results: The translocation of clip was well correlated with diaphragm movement in 90.4% (190/210) of all images. The clip position errors greater than 5 mm were observed in 26.0% in SI, 1.8% in AP, and 5.4% in RL directions, respectively. Moreover, the clip position errors greater than 10 mm were observed in 1.9% in SI, 0.2% in AP, and 0.2% in RL directions, despite respiratory control. Conclusion: Quantitative analysis of surgical clip displacement reflect respiratory motion, setup errors and postoperative change of intraabdominal organ position. Furthermore, position of clips is distinguished easily in verification images. The identification of the surgical clip position may lead to a significant improvement in the accuracy of upper abdominal radiation therapy.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.55-63
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• 2003

The traffic accident is the prerequisite of the traffic accident reconstruction. In this study, the traffic accident (forward collision) and traffic accident reconstruction (inverse collision) simulations are conducted to improve the quality and accuracy of the traffic accident reconstruction. The vehicle and tire models are used to simulate the trajectories for the post-impact motion of the vehicles after collision. The impact dynamic model applicable to the forward and inverse collision simulations is also provided. The accuracy of impact analysis for the vehicular collision depends on the accuracy of the coefficients of restitution and friction. The neural network is used to estimate these coefficients. The forward and inverse collision simulations for the multi-collisions are conducted. The new method fur the accident reconstruction is proposed to calculate the pre-impact velocities of the vehicles without using the trial and error process which requires the repeated calculations of the initial velocities until the forward collision simulation satisfies with the accident evidences. This method estimates the pre-impact velocities of the vehicles by analyzing the trajectories of the vehicles. The vehicle slides on a road surface not only under the skidding during an emergency braking but also under the steering. A vehicle over steering or cornering with excessive speed loses the traction and leaves tile yaw marks on the road surface. The new critical speed formula based on the vehicle dynamics is proposed to analyze the yaw marks and shows smaller errors than ones of the existing critical speed formula.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1904-1926
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• 2016

Iris recognition for biometric personnel identification has gained much interest owing to the increasing concern with security today. The image quality plays a major role in the performance of iris recognition systems. When capturing an iris image under uncontrolled conditions and dealing with non-cooperative people, the chance of getting non-ideal images is very high owing to poor focus, off-angle, noise, motion blur, occlusion of eyelashes and eyelids, and wearing glasses. In order to improve the accuracy of iris recognition while dealing with non-ideal iris images, we propose a novel algorithm that improves the quality of degraded iris images. First, the iris image is localized properly to obtain accurate iris boundary detection, and then the iris image is normalized to obtain a fixed size. Second, the valid region (iris region) is extracted from the segmented iris image to obtain only the iris region. Third, to get a well-distributed texture image, bilinear interpolation is used on the segmented valid iris gray image. Using contrast-limited adaptive histogram equalization (CLAHE) enhances the low contrast of the resulting interpolated image. The results of CLAHE are further improved by stretching the maximum and minimum values to 0-255 by using histogram-stretching technique. The gray texture information is extracted by 1D Gabor filters while the Hamming distance technique is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. Results of the proposed method outperformed other methods in terms of equal error rate (EER).

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.2
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• pp.163-171
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• 2020

Engaged in trawling in limited fishing grounds with a number of fish schools could cause collisions between fishing vessels. Therefore, providing accurate maneuver information according to the situation could be regarded as essential for improving seafarers safety and fishing efficiency as well as safety of navigation. It is difficult to obtain all maneuver information through sea trial tests only, so a method through empirical formula is necessary. Since most empirical formulas are developed for merchant ship types, especially the characteristics of hull shape parameter like C_bB/L and dC_b/B etc. are clearly different between fishing vessels and merchant ships, this could occur estimation errors. Therefore, in this study, the authors have selected target fishing vessels and merchant ships and analyzed the characteristics of hull shape parameter according to the ship types. Based on this analysis, the empirical formula developed for the merchant ship type has applied to the target fishing vessels; it has verified through the turning motion simulation that the estimation error could be generated. In conclusion, it is necessary to include the characteristics of the hull shape parameter of fishing vessels in the empirical formula in order to apply the empirical formula has developed for merchant ship types to fishing vessel types.

• Journal of ILASS-Korea
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• v.25 no.1
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• pp.8-14
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• 2020

Recently, 1-D model-based engine development using virtual engine system is getting more attention than experimental-based engine development due to the advantages in time and cost. Injection rate profile is the one of the main parameters that determine the start and end of combustion. Therefore, it is essential to set up a sophisticated model to accurately predict the injection rate as starting point of virtual engine system. In this research, procedure of 1-D model setup based on AMESim is introduced to predict the dynamic behavior and injection rate of diesel injector. As a first step, detailed 3D cross-sectional drawing of the injector was achieved, which can be done with help of precision measurement system. Then an approximate AMESim model was provided based on the 3D drawing, which is composed of three part such as solenoid part, control chamber part and needle and nozzle orifice part. However, validation results in terms of total injection quantity showed some errors over the acceptable level. Therefore, experimental work including needle movement visualization, solenoid part analysis and flow characteristics of injector part was performed together to provide more accuracy of 1-D model. Finally, 1-D model with the accuracy of less than 10% of error compared with experimental result in terms of injection quantity and injection rate shape under normal temperature and single injection condition was established. Further work considering fuel temperature and multiple injection will be performed.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.478-484
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• 2002

Linear towed arrays (LTA) have a nonlinear shape due to tow vessel motion, ocean swells and currents. By reasons of nominally linear shape, various towed array shape estimation techniques have been developed since the perturbed shape cause the error in target detection. In this paper,, we propose the beamforming method for the perturbed LTA with simple structure. The proposed method linearizes a nonlinear phase of steering vector with position information measured by two reference sensors. It can be proved using some properties of Markov transition matrix, and iteration number of linearization process is decided by variance of cross phase difference. As a result of computer simulation in the ocean environment, beampattern of the proposed method is almost same with the ideal case in my type of array shape. In the signal-to-noise ratio (SNR) performance simlation, the DOA estimation performance of the proposed beamforming method is evaluated, and the comparison with Bartlett beamformer of the LTA shows that the proposed method can estimate. the spatial characteristic of sources more accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.395-404
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• 2000

A damage detection and assessment algorithm is developed by measuring accelerations at limited locations of a structure under forced vibrations. The developed algorithm applies a time-domain system identification (SI) method that identifies a structure by solving a linearly constrained nonlinear optimization problem for optimal structural parameters. An equation error of the dynamic equilibrium of motion is minimized to estimate optimal parameters. An adaptive parameter grouping scheme is applied to localize damaged members with sparse measured accelerations. Damage is assessed in a statistical manner by applying a time-windowing technique to the measured time history of acceleration. Displacements and velocities at the measured degrees of freedom (DOF) are computed by integrating the measured accelerations. The displacements at the unmeasured DOF are estimated as additional unknowns to the unknown structural parameters, and the corresponding velocities and accelerations we computed by a numerical differentiation. A numerical simulation study with a truss structure is carried out to examine the efficiency of the algorithm. A data perturbation scheme is applied to determine the thresholds lot damage indices and to compute the damage possibility of each member.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.