• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.266-272
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• 2021

Water friendly space refers to a place designated to plan and manage spaces for residents Water friendly activities. Efficient management of river Water friendly parks requires automated GIS data and DB construction of the water friendly facilities. Object-based classification using drone images or aerial images is attracting attention as an efficient means to acquire 3D spatial information in the country. To remove the miscellaneous image included in the extracted outline, a linear simplification of the outline is required, and it is difficult to apply manually, so various automation methods have been developed to overcome this, and among them, the most widely studied and utilized is the linear simplification method. In this study, the suitability of linear simplification algorithms such as Douglas-Peucker, Visvalingam-Whyatt, and Bend-simplify algorithms for the geometric shape of hydrophilic facilities was determined.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.93-103
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• 2005

In this paper, we propose a RST resistant robust logo embedding technique for multimedia copyright protection Geometric manipulations are challenging attacks in that they do not introduce the quality degradation very much but make the detection process very complex and difficult. Watermark embedding in the normalized image directly suffers from smoothing effect due to the interpolation during the image normalization. This can be avoided by estimating the transform parameters using an image normalization technique, instead of embedding in the normalized image. Conventional RST resistant schemes that use full frame transform suffer from the absence of effective perceptual masking methods. Thus, we adopt $8\times8$ block DCT and calculate masking using a spatio-frequency localization of the $8\times8$ block DCT coefficients. Simulation results show that the proposed algorithm is robust against various signal processing techniques, compression and geometrical manipulations.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.923-936
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• 2014

Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.

• Korean Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.224-233
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• 1996

An automatic mesh generation scheme with triangular finite elements on three-dimensional surfaces has been developed. The surface triangulation process is performed as follows. To begin, surfaces with key nodes are transformed to two-dimensional planes and the meshes with triangular elements are constructed in these planes. Finally, the constructed meshes are transformed back to the original 3D surfaces. For the mesh generation, an irregular mesh generation scheme is employed in which local mesh densities are assigned by the user along the boundaries of the analysis domain. For this purpose a looping algorithm combined with an advancing front technique using basic operators has been developed, in which the loops are recursively subdivided into subloops with the use of the best split lines and then the basic operators generate elements. Using the split lines, the original boundaries are split recursively until each loop contains a certain number of key nodes, and then using the basic operators such as type-1 and type-2, one or two triangular elements are generated at each operation. After the triangulation process has been completed for each meshing domain, the resulting meshes are finally improved by smoothing process. Sample meshes are presented to demonstrate the versatility of the algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.8
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• pp.721-728
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• 2014

In this paper, it is proposed a method of optimizing path parameters for large-area laser processing. On-the-fly system is necessary for large-area laser processing of uniform quality. It is developed a MOTF(Marking On-The-Fly) board for synchronizing the stage and scanner. And it is introduced the change of the error due to the change of parameters and algorithm for large-area laser processing. This algorithm automatically generates stage path and a velocity profile using acceleration and deceleration parameters. Since this method doesn't use a G-code, even if without expert knowledge, it has an advantage that can be accessed easily. Angle of one of the square of $350{\times}350mm$ was changed from $50^{\circ}$ to $80^{\circ}$ and analyzed the error corresponding to the value of Ta. It is calculated the value of Ta of the best with a precision of 20um through measurement of accuracy according to the Ta of each angle near the edge.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.168-172
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• 2014

In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a $3{\times}3$ Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.103-116
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• 2013

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound(TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Gabor feature extraction and snake-like contour is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing the contour. A Gabor filter bank for extraction of rotation-invariant texture features has been implemented. A support vector machine(SVM) for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted by the snake-like contour algorithm. A number of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with less than 10.2% of the accuracy which is relative to boundary provided manually by experts.

• IE interfaces
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• v.25 no.3
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• pp.365-375
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• 2012

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for humans. UAVs are currently employed in many military missions and a number of civilian applications. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$_PGA (A-star with Post Smoothing_Parallel Genetic Algorithm) for Multiple UAVs's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and MTSP (Multiple Traveling Salesman Problem). After transforming MRPP into Shortest Path Problem (SPP),$A^*PS$_PGA applies a path planning for multiple UAVs.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.149-158
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• 1994

Nonparametric regression technique using kernel estimator is an attractive alternative that has received some attention, recently. The kernel estimate depends on two quantities which have to be provided by the user : the kernel function and the bandwidth. However, the more difficult problem is how to find an appropriate bandwidth which controls the amount of smoothing (see Silverman, 1986). Thus, in practical situation, it is certainly desirable to determine an appropriate bandwidth in some automatic fashion. Thus, the problem is to find a data-driven or adaptive (i.e., depending only on the data and then directly computable in practice) bandwidth that performs reasonably well relative to the best theoretical bandwidth. In this paper, we introduce a relation between bias and variance of mean square error. Thus, we present a simple and effective algorithm for selecting local bandwidths in kernel regression.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.72-79
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• 2007

In this paper, It propose a new restoration algorithm of high resolution, which is reconstructed to high resolution image using low resolution image informations. The proposed algorithm is constructed based on super resolution theory, it is consisted of progressive steps of the integration and construction. It reduced a lot of data-processing capacity and noise with integration through sub-pixel movement and wavelet basis through a higher resolution. As a result, it is shown that the main information is maintained and the error rate is improved. Using expansion fuzzy wavelet B-spline interpolation in stage of construction, it is confirmed that we can achieve smoothing image and good resolution without blur and block.