• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2007.04a
• /
• pp.243-248
• /
• 2007

This study proposed a procedure to improve the error defection of attached cadastral maps using digital map data. In addition, this study also provided the direction for the accuracy improvement of attached cadastral maps by comparing analysis methods. - such as centroid, Lee Sallee shape index, and area index. The analysis is performed as follows. First, by using centroid measurement, the center point of cadastral maps and attached cadastral maps are compared. Secondly by using Lee Sallee shape measurement, the location accuracy of range area is investigated. Thirdly, by using area measurement, the range area within allowable error scope is verified. Based on analysis, the discrepancy between cadastral maps and the attacked cadastral maps are detected as follows; 98.2% from Lee Sallee shape index, 41.8% from centroid, 15.4% from area index in the whole error.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.881-888
• /
• 1997

A new algorithm for detection of tool fracture in milling process was developed. The variation of the peak-to-valley value of cutting load was used in this algorithm. Various kinds of vectors representing the condition of tool, such as tool condition vector, reference tool condition vector, tool condition variation vector were defined. Using these vectors, tool fracture index which represents the magnitude of tool fracture and is independent of tool run-outs is developed. Small and large tool fracture and chipping under various cutting condition could be detected using proposed tool fracture index, which was proved with cutting force model and experiments.

• Proceedings of the IEEK Conference
• /
• 2000.06d
• /
• pp.238-241
• /
• 2000

A fingerprint core-point detection algorithm is presented in this paper. Core-point is useful for fingerprint classification and also for the fingerprint verification since it giver a reference to a fingerprint. Traditional methods of finding the core-point is introduced. These methods are the method using poincare index and the method using sine component of ridge directions. The proposed method is modified algorithm of the latter using the poincare index. The experimental results show that the proposed algorithm achieves almost the same accuracy with faster speed.

• Journal of the Korean Society for Precision Engineering
• /
• v.24 no.6
• /
• pp.37-44
• /
• 2007

• Journal of Korean Society of Transportation
• /
• v.19 no.2
• /
• pp.73-73
• /
• 2001

• Journal of the Korea Society for Simulation
• /
• v.21 no.4
• /
• pp.91-102
• /
• 2012

Network port scan attack is the method for finding ports opening in a local network. Most existing IDSs(intrusion detection system) record the number of packets sent to a system per unit time. If port scan count from a source IP address is higher than certain threshold, it is regarded as a port scan attack. The degree of risk about source IP address performing network port scan attack depends on attack count recorded by IDS. However, the measurement of risk based on the attack count may reduce port scan detection rates due to the increased false negative for slow port scan. This paper proposes a method of summarizing 4 types of information to differentiate network port scan attack more precisely and comprehensively. To integrate the riskiness, we present a risk index that quantifies the risk of port scan attack by using PCA. The proposed detection method using risk index shows superior performance than Snort for the detection of network port scan.

• Smart Structures and Systems
• /
• v.20 no.4
• /
• pp.427-440
• /
• 2017

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.49 no.3
• /
• pp.37-46
• /
• 2012

In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.

• Spatial Information Research
• /
• v.19 no.5
• /
• pp.37-46
• /
• 2011

In recent years, utilizations of satellite imagery have been extensively conducted in order to obtain accurate information on drought detection in spring season. This research also carried out utilization of satellite imagery through the various vegetation indices such as NDVI(Normalized Difference Vegeation Index), MSI(Moisture Stress Index), MidIR Index, II(Infrared Index) to find better methodology to detect drought phenomena, especially occurring in spring season. For this purpose, Landsat TM(Thematic Mapper) images were used and applied on the Yeong-cheon city. In this study, the characteristics of DN(Digital Number) for each vegetation index is analyzed, and the correlation analysis between indices and DN according to the number of days with no rain is performed. The results shows high correlation between NDVI and MSI and II with positive correlation on MSI, and negative correlation on II. This indicates the possibility for practical use of MSI, II indices with NDVI to obtain better credibility for detecting spring droughts.

• Current Optics and Photonics
• /
• v.4 no.3
• /
• pp.210-220
• /
• 2020

Aiming at the problem that the Local Sparse Difference Index algorithm has low accuracy and low efficiency when detecting target anomalies in a hyperspectral image, this paper proposes a Weighted Collaborative Representation and Sparse Difference-Based Hyperspectral Anomaly Detection algorithm, to improve detection accuracy for a hyperspectral image. First, the band subspace is divided according to the band correlation coefficient, which avoids the situation in which there are multiple solutions of the sparse coefficient vector caused by too many bands. Then, the appropriate double-window model is selected, and the background dictionary constructed and weighted according to Euclidean distance, which reduces the influence of mixing anomalous components of the background on the solution of the sparse coefficient vector. Finally, the sparse coefficient vector is solved by the collaborative representation method, and the sparse difference index is calculated to complete the anomaly detection. To prove the effectiveness, the proposed algorithm is compared with the RX, LRX, and LSD algorithms in simulating and analyzing two AVIRIS hyperspectral images. The results show that the proposed algorithm has higher accuracy and a lower false-alarm rate, and yields better results.