• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.586-591
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• 2009

In this paper, we propose the mobile object tracking algorithm based on the feature vector using particle filter. To do this, first, we detect the movement area of mobile object by using RGB color model and extract the feature vectors of the input image by using the KLT-algorithm. And then, we get the first feature vectors by matching extracted feature vectors to the detected movement area. Second, we detect new movement area of the mobile objects by using RGB and HSI color model, and get the new feature vectors by applying the new feature vectors to the snake algorithm. And then, we find the second feature vectors by applying the second feature vectors to new movement area. So, we design the mobile object tracking algorithm by applying the second feature vectors to particle filter. Finally, we validate the applicability of the proposed method through the experience in a complex environment.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.227-234
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• 2009

The Paper introduces a new technique for block matching motion estimation. since the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the PSNR values are improved as high as 9~32% in terms of average number of search point per motion vector estimation and improved about 0.06~0.21dB on an average except the FS(full search) algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.1000-1010
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• 2006

This paper proposes a new architecture for DCT-based motion estimation and compensation. Previous methods do riot take sufficient advantage of the sparseness of 2-D DCT coefficients to reduce execution time. We first derive a recursion equation to perform DCT domain motion estimation more efficiently; we then use it to develop a wavefront array processor (WAP) consisting of processing elements. In addition, we show that the recursion equation enables motion predicted images with different frequency bands, for example, from the images with low frequency components to the images with low and high frequency components. The wavefront way Processor can reconfigure to different motion estimation algorithms, such as logarithmic search and three step search, without architectural modifications. These properties can be effectively used to reduce the energy required for video encoding and decoding. The proposed WAP architecture achieves a significant reduction in computational complexity and processing time. It is also shown that the motion estimation algorithm in the transform domain using SAD (Sum of Absolute Differences) matching criterion maximizes PSNR and the compression ratio for the practical video coding applications when compared to tile motion estimation algorithm in the spatial domain using either SAD or SSD.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.41-47
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• 2011

Processing of the raw LiDAR data requires the high-end processor, because data form is a vector. In contrast, if LiDAR data is converted into a regular grid pattern by filltering, that has advantage of being in a low-cost equipment, because of the simple structure and faster processing speed. Especially, by using grid data classification, such as Quadtree, some of trees and cars are removed, so it has advantage of modeling. Therefore, this study presents the algorithm for automatic extraction of ground points using Quadtree and refion growing method from LiDAR data. In addition, Error analysis was performed based on the 1:5000 digital map of sample area to analyze the classification of ground points. In a result, the ground classification accuracy is over 98%. So it has the advantage of extracting the ground points. In addition, non-ground points, such as cars and tree, are effectively removed as using Quadtree and region growing method.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.51-58
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• 2008

In this paper, we propose a place modeling based on the distribution of scale-invariant features, and a place recognition method that recognizes places by comparing the place model in a database with the extracted features from input data. The proposed method is based on the assumption that every place can be represented by unique feature distributions that are distinguishable from others. The proposed method uses global information of each place where one place is represented by one distribution model. Therefore, the main contribution of the proposed method is that the time cost corresponding to the increase of the number of places grows linearly without increasing exponentially. For the performance evaluation of the proposed method, the different number of frames and the different number of features are used, respectively. Empirical results illustrate that our approach achieves better performance in space and time cost comparing to other approaches. We expect that the Proposed method is applicable to many ubiquitous systems such as robot navigation, vision system for blind people, wearable computing, and so on.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.103-112
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• 1999

Genetic algorithm, which uses principles of natural selection and population genetics, is an efficient method to find out an optimal solution. In conventional genetic algorithms, however, the size of gene pool needs to be increased to insure a convergency. Therefore, many memory spaces and much computation time were needed. Also, since child chromosomes were generated by chromosome crossover and gene mutation, the algorithms have a complex structure. Thus, in this paper, a compact stereo matching algorithm using a population-based incremental learning based on probability vector is proposed to reduce these problems. The PBIL method is modified for matching environment. Since th proposed algorithm uses a probability vector and eliminates gene pool, chromosome crossover, and gene mutation, the matching algorithm is simple and the computation load is considerably reduced. Even though the characteristics of images are changed, stable outputs are obtained without the modification of the matching algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.90-98
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• 2013

The stereo system based on local matching is very popular due to its algorithmic simplicity, however it is limited to apply to various applications because it shows poor quality with low matching rates. In this paper, we propose and design a realtime stereo system based on an adaptive support-weight and the system shows low error rates and realtime performance. Generally, in the adaptive support-weight algorithm the intermediate computing results can not be reused to reduce the number of computations. In this research we modify the scheduling to reuse the intermediate results for the better performance by processing rows and columns separately. The nonlinear functions such as exponential or arc tangent have been designed with piecewise linear and step functions by empirical simulations and error analysis. The proposed architecture is composed of 9 processing elements for realtime performance. The proposed stereo system has been designed and synthesized using Donbu Hitek 0.18um standard cell library and can run up to 350Mhz operation frequency (33 frames per second) with 424K gates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.805-807
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• 2016

By using ICT in the manufacturing industry with the advent of "Industry 4.0" of Germany, it has been promoted a lot of research to maximize the production capacity. Be particularly increased manufacturing complexity, increase the information delivered to the operator, augmented reality technologies in order to maximize production have been studied. In this paper, in order to solve the deficiencies problem that frequently occurs in the actual site, using the augmented reality technology, provides a system for providing personal training information to the worker. Proposed system, by fusing worker information and process another job, generates educational information of the individual, it is to provide information through the video of the tablet. When using such methods, it is expected that it is possible to improve the production quality of the manufacturing industry to overcome the deficiencies problem that frequently occurs through the continuing education of employees.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.651-661
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• 2014

The complexity to search a specific content over TV platform is drastically increasing. Based on previous studies from computer data management system, we propose a new method that helps users to search and select content effectively. In general, contents over computers are represented by spatial metaphor, which replicates our physical environment and value systems about space. We suggest 3D lattice structure to construct information space for TV platform. Users can infer relevance between contents via special clue in information space, so as to select content more easily. Also, they can search contents through its temporal property that also represented in space. We make full use of our natural capability that can reduce additional overload to learning new interface. The results of this study can be significant and heuristic contributions, as they can be applied to diverse service areas utilizing video contents.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.75-82
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• 2017

Recently, as the roles and utilization fields of UAV become more diverse, demand for high - level mission has been increasing. To solve this issue, researches on the operation of multiple small UAVs and related systems have been actively carried out. The multiple small UAVs based application system has a problem that the task complexity of control personnel increases because the control personnel must continuously control and manage several small UAVs. Hence, it is necessary to develop a software platform that can perform efficient control in order to employ a multiple small UAVs based application system successfully. In this paper, we propose an effective ground control software platform for application systems using multiple small UAVs. We first analyze the requirements for the software platform, and design and implement software based on the analysis. Simulation using the X-plane flight simulator shows that multiple flight data are effectively displayed and that the image data transmitted from many small UAVs are simultaneously displayed in real time.