• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1474-1486
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• 2010

In this paper, we propose an algorithm which represents the distance depiction technique of real painting that named "Aerial Perspective" in painterly rendering. It is a painting technique that depicts the attenuations of light in the atmosphere, and the scattering effect is changed by the distance, altitude and density of atmospheres. For the reflection of these natures, we use the depth information corresponding to an input image and user-defined parameters, so that user changes the effect level. We calculate the distance and altitude of every pixel with the depth information and parameters about shot information, and control the scattering effects by expression parameters. Additionally, we accentuate the occluding edges detected by the depth information to clarify the sense of distance between fore and back-ground. We apply our algorithm on various landscape scenes, and generate the distance-emphasized results compared to existing works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.287-292
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• 2015

In this paper, we evaluated the performance of D2D advertisement dissemination algorithms with maximum-distance and transmission-efficiency based relay selections with respect to the total number of successfully received users and transmission efficiency. To assume more practical environment, we took into account pre-defined target-areas based on the information of user density and the limit for the maximum number of relay users. Through the simulations we compared the performance results of both D2D advertisement dissemination algorithms with maximum-distance and transmission-efficiency based relay selections according to increment of the number of sectors. And then, we analysed the superiority of algorithm with transmission-efficiency based relay selections more than maximum-distance based relay selections.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.265-272
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• 2005

In this paper, we propose a technique which is speedily searching for correspondent points of two images using Voronoi-Distance, as an image registration method for feature based image mosaics. It extracts feature points in two images by the SUSAN corner detector, and then create not only the Voronoi Surface which has distance information among the feature points in the base image using a priority based Voronoi distance algorithm but also select the model area which has the maximum variance value of coordinates of the feature points in the model image. We propose a method for searching for the correspondent points in the Voronoi surface of the base image overlapped with the model area by use of the partitive search algorithm using queues. The feature of the method is that we can rapidly search for the correspondent points between adjacent images using the new Voronoi distance algorithm which has $O(width{\times}height{\times}logN)$ time complexity and the the partitive search algerian using queues which reduces the search range by a fourth at a time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.104-113
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• 2022

In this paper, we propose deep learning-based target distance and velocity estimation technique for OFDM radar systems. In the proposed technique, the 2D periodogram is obtained via 2D fast Fourier transform (FFT) from the reflected signal after removing the modulation effect. The periodogram is the input to the conventional and proposed estimators. The peak of the 2D periodogram represents the target, and the constant false alarm rate (CFAR) algorithm is the most popular conventional technique for the target's distance and speed estimation. In contrast, the proposed method is designed using the multiple output convolutional neural network (CNN). Unlike the conventional CFAR, the proposed estimator is easier to use because it does not require any additional information such as noise power. According to the simulation results, the proposed CNN improves the mean square error (MSE) by more than 5 times compared with the conventional CFAR, and the proposed estimator becomes more accurate as the number of transmitted OFDM symbols increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1163-1168
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• 2001

The ranging systems measure range data in three-dimensional coordinate from target surface. These non-contact remote ranging systems is widely used in various automation applications, including military equipment, construction field, navigation, inspection, assembly, and robot vision. The active ranging systems using time of flight technique or light pattern illumination technique are complex and expensive, the passive systems based on stereo or focusing principle are time-consuming. The proposed algorithm, that is based on cross correlation of projection profile of vertical edge, provides advantages of fast and simple operation in the range acquisition. The results of experiment show the effectiveness of the proposed algorithm.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.32-41
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• 1999

In spatial database system, the nearest neighbor query occurs frequently and requires the processing cost higher than other spatial queries do. The number of nodes to be searched in the index can be minimized for optimizing the cost of processing the nearest neighbor query. The optimal search distance is pr9posed for the measurement of a search distance to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we prove properties of the optimal search distance in N-dimensional. We show through experiments that the performance of query processing of our method is superior to other method using maximum search distance.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.19-26
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• 2012

To resist the relay attacks in RFID system, it is commonly used RFID distance bounding protocols using the round trip time measurement for 1 bit challenge and response between a reader and a tag. If the success probability of relay attacks for the 1 bit challenge and response can be reduced in these protocols, it is possible to make an efficient distance bounding protocol. In this paper, we propose an efficient RFID distance bounding protocol based on 2 bit challenge and response which is modified the RFID distance bounding protocol proposed by Hancke and Khun based on 1 bit challenge and response. The success probability of relay attack for the proposed protocol is (7/16)n for the n times of challenge and response, which is much lower than (3/4)n given by Hancke and Khun's protocol.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.85-88
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• 2009

In multimedia database systems, the nearest neighbor Query occurs frequently and requires the processing cost higher than other spatial Queries do. It needs the measurement of search distance that the number of searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the nearest neighbor query. The circular location property of objects is considered to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of nearest neighbor queries be considered a circular location property of object where the search space consists of a circular domain and show its characteristics. The proposed method uses the circular minimum distance and the circular optimal distance, the search measurement for optimizing the processing cost of nearest neighbor queries.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.75-80
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• 2008

This paper proposes a method to detect scene change using global decision tree that extract boundary cut that have width of big change that happen by camera brake from difference value of frames. First, calculate frame difference value through regional X2-histogram and normalization, next, calculate distance between difference value using normalization. Shot boundary detection is performed by compare global threshold distance with distance value for two adjacent frames that calculating global threshold distance based on distance between calculated difference value. Global decision tree proposed this paper can detect easily sudden scene change such as motion from object or camera and flashlight.