• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.233-246
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• 2003

This paper presents a methodology to account for the partial or gradual changes of environmental phenomena in categorical map information for the fusion/integration of multiple spatial data. The fuzzy set based spatial data fusion scheme is applied in order to account for the fuzziness of boundaries in categorical information showing the partial or gradual environmental impacts. The fuzziness or uncertainty of boundary is represented as two kinds of fuzzy membership functions based on fuzzy object concept and the effects of them are quantitatively evaluated with the help of a cross validation procedure. A case study for landslide hazard assessment demonstrates the better performance of this scheme as compared to traditional crisp boundary representation.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.521-524
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• 2005

This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.82-89
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• 2014

In this study, the metallurgical analysis and mechanical property measurement have been performed to investigate the effect of long-term thermal aging on the microstructural evolution in the fusion boundary region between weld metal and low alloy steel in dissimilar metal welds. A representative dissimilar weld mock-up made of Alloy 690-Alloy 152-A533 Gr. B was fabricated and aged at $450^{\circ}C$ for 2,750 hours. The microstructural characterization was conducted mainly near in a weld root region by using optical microscopy, scanning electron microscopy, transmission electron microscopy. And the mechanical properties were measured with Vickers microhardness test and nanoindentation method. A steep gradient was shown in the chemical composition profile across the interface between A533 Gr. B and Alloy 152. Type-II boundaries were found in weld side of DMW and the hardness was the highest at the narrow zone between Type-II boundary and fusion boundary.

• Journal of Welding and Joining
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• v.4 no.1
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• pp.40-46
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• 1986

This investigation studied the toughness variations in the narrow gap weldment with the notch location. Specimens with the notch at the center of the weld metal showed the lowest toughness. As the location of notchmoves to fusion line, the impact properties improve reaching a maximum at the fusion boundaries. This improvement in toughness can be explained by the microstructural feature showing in the narrow gap weldment. "one pass/layer" technique performed in narrow gap welding results in the increased proportion of refined structure as approaching to fusion boundary from weld center and thus leave 100% refined structure along the fusion boundary. HAZ also shows 100% refined structure with respect to base metal structure accompanied with the significant suppression of ductile-brittle transition temperature.mperature.

• Nuclear Engineering and Technology
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• v.44 no.6
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• pp.673-682
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• 2012

Three dimensional atom probe tomography (3D APT) is applied to characterize the dissimilar metal joint which was welded between the Ni-based alloy, Alloy 690 and the low alloy steel, A533 Gr. B, with Alloy 152 filler metal. While there is some difficulty in preparing the specimen for the analysis, the 3D APT has a truly quantitative analytical capability to characterize nanometer scale particles in metallic materials, thus its application to the microstructural analysis in multi-component metallic materials provides critical information on the mechanism of nanoscale microstructural evolution. In this study, the procedure for 3D APT specimen preparation was established, and those for dissimilar metal weld interface were prepared near the fusion boundary by a focused ion beam. The result of the analysis in this study showed the precipitation of chromium carbides near the fusion boundary between A533 Gr. B and Alloy 152.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.266-274
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• 2003

Distance Fourier descriptors of local target boundary and feature information fusion using multiple MLPs (Multilayer perceptrons) are proposed. They are used to identify nonoccluded and partially occluded targets in natural FLIR (forward-looking infrared) images. After segmenting a target, radial Fourier descriptors as global shape features are defined from the target boundary. A target boundary is partitioned into four local boundaries to extract local shape features. In a local boundary, a distance function is defined from boundary points and a line between two extreme points. Distance Fourier descriptors as local shape features are defined by using distance function. One global feature vector and four local feature vectors are used as input data for multiple MLPs to determine final identification result of the target. In the experiments, we show that the proposed method is superior to the traditional feature sets with respect to the identification performance.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.35-45
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• 2016

To resolve the problems of Poisson/impulse noise, blurriness, and sharpness in degraded X-ray images, a novel and efficient enhancement algorithm based on X-ray image fusion using a discrete wavelet transform is proposed in this paper. The proposed algorithm consists of two basics. First, it applies the techniques of boundary division to detect Poisson and impulse noise corrupted pixels and then uses the Wiener filter approach to restore those corrupted pixels. Second, it applies the sharpening technique to the same degraded X-ray image. Thus, it has two source X-ray images, which individually preserve the enhancement effects. The details and approximations of these sources X-ray images are fused via different fusion rules in the wavelet domain. The results of the experiment show that the proposed algorithm successfully combines the merits of the Wiener filter and sharpening and achieves a significant proficiency in the enhancement of degraded X-ray images exhibiting Poisson noise, blurriness, and edge details.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1907-1928
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• 2024

In recent years, multi-focus image fusion has emerged as a prominent area of research, with transformers gaining recognition in the field of image processing. Current approaches encounter challenges such as boundary artifacts, loss of detailed information, and inaccurate localization of focused regions, leading to suboptimal fusion outcomes necessitating subsequent post-processing interventions. To address these issues, this paper introduces a novel multi-focus image fusion technique leveraging the Swin Transformer architecture. This method integrates a frequency layer utilizing Wavelet Transform, enhancing performance in comparison to conventional Swin Transformer configurations. Additionally, to mitigate the deficiency of local detail information within the attention mechanism, Convolutional Neural Networks (CNN) are incorporated to enhance region recognition accuracy. Comparative evaluations of various fusion methods across three datasets were conducted in the paper. The experimental findings demonstrate that the proposed model outperformed existing techniques, yielding superior quality in the resultant fused images.

• Journal of Welding and Joining
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• v.25 no.4
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• pp.1-3
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• 2007