• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2162-2176
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• 2018

Chemical reactions have an intricate relationship with the search for better-quality neighborhood solutions to optimization problems. A catalytic reaction for chemical reactions provides a clue and a framework to solve complicated optimization problems. The application of a catalytic reaction reveals new information hidden in the optimization problem and provides a non-intuitive perspective. This paper proposes a new simulated catalytic reaction method for search in optimization problems. In the experiments using this method, significantly improved results are obtained in almost all graphs tested by applying to a graph bisection problem, which is a representative problem of combinatorial optimization problems.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.593-596
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• 1994

When a force impulse acting on a massive and plex object is measured with a dynamometer, be resonant vibration of the measurement system often leads to serious inaccuracies. A more accurate measurement is obtained when the transfer function ,of the object-dynamometer system is used to compensate for the error in the dynamometer's output signal. The natural frequency and the damping coefficient of the transfer function are estimated by analyzing the waveform of the free damped vibration period after the loading of the force has ended. The residue of the system is determined such that the compensated force spectrum becomes smooth within a neighborhood of the natural frequency. The effectiveness of this signal processing method is experimentally tested on a hammer impulse, under the assumption that the hammer's high resonant frequency accurately models the problems encountered in force impact measurement. The compensation method is used to derive a improved estimate of the hammer impulse.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.701-709
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• 2015

Image stitching method is a technique for obtaining an high-resolution image by combining two or more images. In X-ray image for clinical diagnosis, the size of the imaging region taken by one shot is limited due to the field-of-view of the equipment. Therefore, in order to obtain a high-resolution image including large regions such as a whole body, the synthesis of multiple X-ray images is required. In this paper, we propose a rapid stitching method of digital X-ray images using template-based registration. The proposed algorithm use principal component analysis(PCA) and k-nearest neighborhood(k-NN) to determine the location of input images before performing a template-based matching. After detecting the overlapping position using template-based matching, we synthesize input images by alpha blending. To improve the computational efficiency, reduced images are used for PCA and k-NN analysis. Experimental results showed that our method was more accurate comparing with the previous method with the improvement of the registration speed. Our stitching method could be usefully applied into the stitching of 2D or 3D multiple images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.656-664
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• 2006

In this paper, we introduce a new LUT based watermarking method for a halftone image. Watermark bits are hidden at pseudo-random locations of halftone image in the proposed method. The pixel values of the halftone image are determined from the LUT entry indexed by both the neighborhood halftone pixels and current grayscale value. The LUT is trained by a set of grayscale images and corresponding halftone images. Advantage of the LUT method is that it can be executed very fast compared with other watermarking methods for a halftone image. Therefore, the algorithm can be embedded in a printer. Experiments for real scanned images showed that the method is a feasible method to hide the large amount of data within a halftone image without noticeable distortion and comparing to the DHED method, is almost same in quality but significantly shorten in processing time.

• Fisheries and Aquatic Sciences
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• v.4 no.1
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• pp.1-9
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• 2001

This paper describes a procedure extracting feature vector of a target cell more precisely in the case of identifying specified cell. The classification of object type is based on feature vector such as area, complexity, centroid, rotation angle, effective diameter, perimeter, width and height of the object So, the feature vector plays very important role in classifying objects. Because the feature vectors is affected by noises and holes, it is necessary to remove noises contaminated in original image to get feature vector extraction exactly. In this paper, we propose the following method to do to get feature vector extraction exactly. First, by Otsu's optimal threshold selection method and morphological filters such as cleaning, filling and opening filters, we separate objects from background an get rid of isolated particles. After the labeling step by 4-adjacent neighborhood, the labeled image is filtered by the area filter. From this area-filtered image, feature vector such as area, complexity, centroid, rotation angle, effective diameter, the perimeter based on chain code and the width and height based on rotation matrix are extracted. To prove the effectiveness, the proposed method is applied for yeast Zygosaccharomyces rouxn. It is also shown that the experimental results from the proposed method is more efficient in measuring feature vectors than from only Otsu's optimal threshold detection method.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.4
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• pp.37-47
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• 2014

This study aims to examine the usage of and satisfaction with neighborhood parks and university campuses and compare through the RPRS analysis of them to figure out how university campuses, as substitutive green spaces, play the role of curative environment for neighboring people. This study relied on two methods: a descriptive method of researching publications and related scholastic writings and an empirical study of researching how the park and campus has been utilized and researching whether the residents are satisfied with the currently existing space and the environment or not, and finally researching how the university campus open space as a curative environment impacts the satisfaction and utilization through reliability analysis. As a result, contribution of healing environment has a relatively high average contribution of 4 or more points, respectively. These results suggest that urban people think that a relationship between man and nature is very important in the overabundance of stress in modern society. It shows that neighborhoods are higher than university campuses in the explanatory of the Attention Restoration Theory, but the campus is higher than the neighborhood park in similarity of configuration. The result of RPRS analysis shows that the therapeutic qualities of the landscape may be very useful to evaluate a college campus open space in "the Revised Perceived Restoration Scale." The results showed that, in future studies, it will be a great help by widespread use of pre-evaluation of the characteristics of restorative environments in the planning, design and other works. To study the impact of the curative features on evaluating future research locations, the location should provide a variety of purposes and motives. At the same time, it should provide specific design ideas to design-related designers by using perceived restoration scale.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.12
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• pp.863-870
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• 2012

The market trends of automatic meter reading associated with smart water meters were investigated. Also, recent developments and field applications of key technology for automatic meter reading associated with smart water meters were analyzed. Smart water meters have been manufactured mostly in United States and Europe and have been expanded their business to Asia. Integrated water management system combining with the additional functions such as real-time consumption metering, cost notification, water conservation, leak detection, water quality monitoring, and flow control have been operated in automatic meter reading. Both water quality and quantity data measured from smart water meters and sensors were transferred to data concentration units through neighborhood area network, and then were transferred to integrated server through wide area network. The data transfer methods were determined by comprehensively considering urban scale, density of smart water meters, power supply and network topologies. Common data collection methods such as fixed network to data concentation units, vehicles drive by, people walk by, and drone fly by have been applied. The automatic meter reading associated with smart water meters are spread throughout the world, and both water and energy savings result in saving the money and reducing the greenhouse gases emission.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.10-16
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• 2007

In this paper, we propose a technique for retrieving images using spatial color correlation and texture characteristics based on local fourier transform. In order to retrieve images, two new descriptors are proposed. One is a color descriptor which represents spatial color correlation. The other is a descriptor combining the proposed color descriptor with texture descriptor. Since most of existing color descriptors including color correlogram which represent spatial color correlation considered just color distribution between neighborhood pixels, the structural information of neighborhood pixels is not considered. Therefore, a novel color descriptor which simultaneously represents spatial color distribution and structural information is proposed. The proposed color descriptor represents color distribution of Min-Max color pairs calculating color distance between center pixel and neighborhood pixels in a block with 3x3 size. Also, the structural information which indicates directional difference between minimum color and maximum color is simultaneously considered. Then new color descriptor(min-max color correlation descriptor, MMCCD) containing mean and variance values of each directional difference is generated. While the proposed color descriptor includes by far smaller feature vector over color correlogram, the proposed color descriptor improves 2.5 % ${\sim}$ 13.21% precision rate, compared with color correlogram. In addition, we propose a another descriptor which combines the proposed color descriptor and texture characteristics based on local fourier transform. The combined method reduces size of feature vector as well as shows improved results over existing methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.35-44
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• 2015

The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.571-582
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• 2008

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.