• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.281-286
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• 2010

We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1951-1959
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• 2016

In this paper, we propose a two-scale fusion method for infrared and visible images using saliency and variance. The images are separated into two scales respectively: a base layer of low frequency component and a detailed layer of high frequency component. Then, these are synthesized using weight. The saliencies and the variances of the images are used as the fusion weights for the two-scale images. The proposed method is tested on several image pairs, and its performance is evaluated quantitatively by using objective fusion metrics.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.75-86
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• 2012

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.39-45
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• 2009

In this paper we present a cleaning robot system for an autonomous mobile robot. Our robot performs goal reaching tasks into unknown indoor environments by using sensor fusion. The robot's operation objective is to clean floor or any other applicable surface and to build a map of the surrounding environment for some further purpose such as finding the shortest path available. Using its cleaning robot system for an autonomous mobile robot can move in various modes and perform dexterous tasks. Performance of the cleaning robot system is better than a fixed base redundant robot in avoiding singularity and obstacle. Sensor fusion using the clean robot improves the performance of the robot with redundant freedom in workspace and Map-Building. In this paper, Map-building of the cleaning robot has been studied using sensor fusion. A sequence of this alternating task execution scheme enables the clean robot to execute various tasks efficiently. The proposed algorithm is experimentally verified and discussed with a cleaning robot, KCCR.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.792-797
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• 2002

In the following paper two algorithms, suitable for the analysis of panchromatic data as provided by KOMPSAT-1 will be presented. One is a texture analysis which will be used to create a settlement mask based on the variations of gray values. The other is a fusion algorithm which allows the combination of high resolution panchromatic data with medium resolution multispectral data. The procedure developed for this purpose uses the spatial information present in the high resolution image to spatially enhance the low resolution image, while keeping the distortion of the multispectral information to a minimum. This makes it possible to use the fusion results for standard multispecatral classification routines. The procedures presented here can be automated to large extent, making them suitable for a standard processing routine of satellite data.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.258-261
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• 2011

오늘날 에너지를 확보와 관련하여 많은 세계 각국 및 기업에서 다양한 사업과 다양한 실험이 이루어지고 있다. 최근 이와 관련하여 미래의 청정 에너지로 부각되고 있는 핵융합에너지가 관심을 받고 있으며, 국내에서도 많은 연구와 성과가 나타나고 있다. 하지만, 이들 연구성과들을 제대로 관리하여 다른 연구에 재투자할 수 있는 지식관리가 부족한 형편이다. 단순한 지식관리보다는 조직의 비즈니스, 정보, 응용 시스템 및 기반구조에 맞도록 적용하여 적시적소에 이용 가능한 시스템을 구성할 필요가 있다. 따라서 본 연구에서는 핵융합에너지 관련 지식 데이터를 적절하게 관리할 수 있는 개념수준의 포털기반 핵융합 에너지 지식관리시스템의 설계를 제안한다.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.671-682
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• 2012

Strong backscattering features from high-resolution Synthetic Aperture Rader (SAR) image provide useful information to analyze earth surface characteristics such as man-made objects in urban areas. The SAR image has, however, some limitations on description of detail information in urban areas compared to optical images. In this paper, we propose a new classification method using a fused SAR and Electro-Optical (EO) image, which provides more informative classification result than that of a single-sensor SAR image classification. The experimental results showed that the proposed method achieved successful results in combination of the SAR image classification and EO image characteristics.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.63-65
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• 2012

플라즈마 물성데이터는 플라즈마 내에서 일어나는 입자(전자, 원자, 이온분자 등) 들의 충돌에 의해 발생되는 데이터로써 플라즈마 현상을 이해하는 필수 데이터이며, 다양한 분야에서 응용되고 있다. 플라즈마 물성데이터를 산업계에서 지속적으로 참조하여 사용할 수 있도록 만든 수치데이터나 통계자료를 플라즈마 물성 참조데이터라고 한다. 기존 플라즈마 물성데이터 센터의 플라즈마 물성 참조데이터 수집평가 시스템은 사용자가 이용하고자 하는 플라즈마 물성 참조데이터를 일일이 자신의 시스템에 맞춰 데이터를 다시 가공해야 하는 어려움이 있어 데이터를 효율적인 관리하고 다양한 분야에 적용하기 위한 XML Schema 설계 대해 논의한다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.345-349
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• 2007

과학연구 분야에서는 부단히 새로운 연구 과제를 제기되고 있으며 이에 대한 연구조건 및 연구방법을 다각도로 변화시키면서 보다 효과적인 연구결과를 얻기 위한 노력을 거듭하고 있다. 이와 같은 연구활동이 활발히 진행됨에 따라 급증하는 데이터를 효율적으로 관리할 필요성이 증가하였으며 다양한 데이터 저장소에 저장되어 있는 다량의 데이터를 통합관리하기 위한 연구가 계속되어 왔다. 이런 연구를 진행함에 있어서 데이터를 효율적으로 관리하고 데이터 구조, 형태의 변화에 유연하게 대처하기 위해서는 데이터모델 관리가 필요하다. 본 논문에서는 사용자로 하여금 다양한 저장소의 데이터 모델을 관리하고 이로부터 동적으로 데이터를 생성하여 통합 관리할 수 있는 XML Schema 관리 툴을 제공한다.