• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4429-4447
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• 2018

Local binary descriptors are well-suited for many real-time and/or large-scale computer vision applications, while their low computational complexity is usually accompanied by the limitation of performance. In this paper, we propose a new optimization framework, RLDB (Robust-LDB), to improve a typical region-based binary descriptor LDB (local difference binary) and maintain its computational simplicity. RLDB extends the multi-feature strategy of LDB and applies a more complete region-comparing configuration. A cascade bit selection method is utilized to select the more representative patterns from massive comparison pairs and an online learning strategy further optimizes descriptor for each specific patch separately. They both incorporate LDP (linear discriminant projections) principle to jointly guarantee the robustness and distinctiveness of the features from various scales. Experimental results demonstrate that this integrated learning framework significantly enhances LDB. The improved descriptor achieves a performance comparable to floating-point descriptors on many benchmarks and retains a high computing speed similar to most binary descriptors, which better satisfies the demands of applications.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.283-292
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• 2006

Interest about a latest security connection technology rises, and try to overcome security vulnerability Certification about on-line user methods through fingerprint that is biometries information apply. In this study, designs and implements fingerprint recognition system that is invariant to rotation by fingerprint recognition system for certification about on-line user. Proposed method focused in matching process through pre-process of fingerprint image, feature point extraction. Improved process time and correct recognition rate in fingerprint recognition system that is invariant to rotation presented in existing study. Also, improved noise, distortion problems that happen in preprocess of existing study applying directional Laplacian filter.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.2
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• pp.24-29
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• 1993

This paper describes a method for generating an initial hull form by using form parameters. As a mathematical representation of curves, B-spline curves are used as well as the polynomials used by Durand et al. The five basic control curves and the centerline contour are defined to give the boundary conditions for body plan by using above mentioned mathematical models. From these curves body plan is determined. Two additional curves which are concerned the position of matching point between the cylindrical form and the water line are proposed to get the preliminary faired water lines.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.602-608
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• 2015

This paper proposes an algorithm for precise detection of corner points on a coplanar checkerboard in order to perform stereo camera calibration using a single frame. Considering the conditions of automobile production lines where a stereo camera is attached to the windshield of a vehicle, this research focuses on a coplanar calibration methodology. To obtain the accurate values of the stereo camera parameters using the calibration methodology, precise localization of a large number of feature points on a calibration target image should be ensured. To realize this demand, the idea with respect to a checkerboard pattern design and the use of a Homography matrix are provided. The calibration result obtained by the proposed method is also verified by comparing the depth information from stereo matching and a laser scanner.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.67-76
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• 2000

In this paper, a low noise amplifier has been developed, which is operating at L-band i.e., 1525-1575 MHz. By using resistive decoupling circuits, the resistor dissipates undesired signal in low frequency band. By adopting this design method the stability of the LNA is increased and the input impedance matching is improved. The LNA consists of the low noise GaAs FET ATF-10136 and the internally matched VNA-25. The low LNA is fabricated by both the RP circuit and the self-bias circuits in an aluminum housing. As a result, the characteristics of the LNA implemented show more than 32 dB in gain, lower than 0.5 dB in noise figure, 18.6 dBm output gain in 1 dB gain compression point.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.102-109
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• 1999

In this paper, Electromagnetic scattering problem by a perfectly conducting strip grating with 2 dielectric layer on a grounded plane by incidence of a electric wave is analyzed by applying the PMM (Point Matching Method) known as a simple procedure. The scattered electromagnetic fields are expanded in a series of Floquet mode functions. The boundary conditions are applied to obtain the unknown field coefficients and the conducting boundary condition is used for the relationship between the tangential electric field and the electric current density on the strip When the incident angle is normal incidence the minimum value of the geometrically normalized reflected power according as relative permittivity is increased it should be noted that the value of the strip width gets moved toward high value. Them most energy by a normal incident wave is scattered in direction of the other angles except normal incident angle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.65-73
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• 2019

In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.230-236
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• 2018

3D depth perception has played an important role in robotics, and many sensory methods have also proposed for it. As a photodetector for 3D sensing, single photon avalanche diode (SPAD) is suggested due to sensitivity and accuracy. We have researched for applying a SPAD chip in our fusion system of time-of-fight (ToF) sensor and stereo camera. Our goal is to upsample of SPAD resolution using RGB stereo camera. Currently, we have 64 x 32 resolution SPAD ToF Sensor, even though there are higher resolution depth sensors such as Kinect V2 and Cube-Eye. This may be a weak point of our system, however we exploit this gap using a transition of idea. A convolution neural network (CNN) is designed to upsample our low resolution depth map using the data of the higher resolution depth as label data. Then, the upsampled depth data using CNN and stereo camera depth data are fused using semi-global matching (SGM) algorithm. We proposed simplified fusion method created for the embedded system.