• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.871-876
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• 2006

In this thesis, to accurately measure 3D face information using the spatial encoding patterns, the new algorithm to segment the pattern images from initial face pattern image is proposed. If the obtained images is non-homogeneous texture and ambiguous boundary pattern, the pattern segmentation is very difficult. Furthermore. the non-encoded areas by accumulated error are occurred. In this thesis, the FCM(fuzzy c-means) clustering method is proposed to enhance the robust encoding and segmentation rate under non-homogeneous texture and ambiguous boundary pattern. The initial parameters for experiment such as clustering class number, maximum repetition number, and error tolerance are set with 2, 100, 0.0001 respectively. The proposed pattern segmentation method increased 8-20% segmentation rate with conventional binary segmentation methods.

• ETRI Journal
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• v.31 no.5
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• pp.593-597
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• 2009

In this paper, we present a spatial perturbation method to control the optical patterns in semiconductor microresonators in the far-field configuration. We propose a fast all-optical switch which operates at a low light level. The switching beam controls the behavior of output beams with strong intensities. The method has been applied successfully to different optical patterns such as rolls, squares, and hexagons.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.642-645
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• 2009

Brain Computer Interface (BCI) is a communication pathway between devices (computers) and human brain. It treats brain signals in real-time basis and discriminates some information of what human brain is doing. In this work, we develop a EEG BCI system using a feature extraction such as common spatial pattern (CSP) and a classifier using Fisher linear discriminant analysis (FLDA). Two-class EEG motor imagery movement datasets with both cued and uncued are tested to verify its feasibility.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.117-119
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• 2006

In this work, we suggest another method to localize DFT in spatial domain. This enables DFT algorithm to be used for local pattern matching. Once calculated, it costs same load to calculate localized DFT regardless of the size or the position of local region In spatial domain. We applied this method to face detection problem and got the results which prove the utility of our method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.16 no.4
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• pp.249-256
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• 2012

In this work, we analyze the spatial patterns of a predator-prey system with cross diffusion. First we get the critical lines of Hopf and Turing bifurcations in a spatial domain by using mathematical theory. More specifically, the exact Turing region is given in a two parameter space. Our results reveal that cross diffusion can induce stationary patterns which may be useful in understanding the dynamics of the real ecosystems better.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.387-388
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• 2007

In this paper, a content-based image retrieval method considering both local information and spatial correlation of image is proposed. In order to efficiently represent the spatial correlation, texture structure is classified into three kinds of pattern. In experiment result, our method improves $3.94%{\sim}11.23%$ precision rate over the existing methods.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.29-36
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• 2001

This paper proposes an efficient image description method for image retrieval using circular scanning pattern. Therefore, we place the origin of the circular scanning pattern on center point of an image and describe spatial color features of the image using the pattern. The features are Circular Dominant Color, Circular Color Texture, and Circular Color Variation Plot. By the method we can describe color and spatial information of the image at a time, efficiently. Therefore, we can reduce the computational expense and memory usage needed to index the image more than the conventional one does.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.313-319
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• 2010

GNSS receiver which uses the weak satellite signal is very vulnerable to the intentional jamming or non-intentional electromagnetic interference. One of the best method to overcome this disadvantage is to use an adaptive array antenna which has the capability of beamforming or nulling to the certain direction. In this paper, the performance of spatial adaptive null pattern control algorithm of 5 element array antenna is analyzed. A control algorithm which is designed in the 5 element array antenna is OPM(Output Power Minimization) which is eliminating the correlation characteristics between a reference antenna and the others. This algorithm can be applied effectively to the satellite navigation's CRPA because the satellite direction is not considered and GNSS signal power is below the thermal noise. The feature of the OPM algorithm is analyzed and the performance is compared with other null pattern control algorithm.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.532-535
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• 2003

In this paper, we propose a new algorithm that can enhance the speed of template matching of hand vascular pattern person verification or recognition system. Various template matching algorithms have advantages in the matching accuracy, but most of the algorithms suffer from computational burden. To reduce the computational amount, with accuracy maintained, we propose following template matching scenario as follows. firstly, original hand vascular image is re-sampled in order to reduce spatial resolution. Secondly, reconstructed image is projected to vertical and horizontal direction, being converted to two one dimensional (1D) data. Thirdly, converted data is used to estimate spatial discrepancy between stored template image and target image. Finally, matching begins from where the estimated order is highest, and finishes when matching decision function is computed to be over certain threshold. We've applied the proposed algorithm to hand vascular pattern identification application for biometrics, and observed dramatic matching speed enhancement. This paper presents detailed explanation of the proposed algorithm and evaluation results.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.632-647
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• 2007

Lots of geographic phenomena have dynamic spatial patterns with time changes, and there have been lots of researches on exploring these dynamic spatial patterns. However, most of these researches focused on the static pattern analysis in a given period, rather than dealing with dynamic changes in the spatial pattern over time with the continual or cumulative perspective. For this reason, investigation of the inertia of spatial process in terms of temporal changes is needed. From this background, the purpose of this paper is to propose the methodology to explore the changes in spatial pattern cumulatively by considering the inertia of the spatial statistics over time, and to apply it to the case study That is, we introduce the new spatial statistic, and produce the z-values of the statistic using Monte Carlo Simulation, and then to explore the changes in spatial patterns over time cumulatively. To do this, the method to combine the J statistic with CUSUM statistic for exploring spatial patterns, and to apply it to the changes in the commercial landuse in Erie County, New York State. Through the proposed method for spatio-temporal Patterns, we could explore continual changes effectively in the spatial patterns reflecting the statistics by temporal spot cumulatively.