• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.735-741
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• 2014

Edge in images appears when a great difference shows up in light and shade between pixels and includes data of the subject's size, location direction and etc. The edge is generally detected by the methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) and etc. However, in AWGN(additive white Gaussian noise) added images, quality of the edge becomes slightly uncertain. Therefore, this paper proposed edge detection algorithm using modified mask of weighting to improve the quality of the existing methods. And in order to verify the performance efficiency of the proposed method, processed image and PFOM(Pratt's figure of merit) has been used as valuation standard for a comparison with the existing methods.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.569-584
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• 2009

Edge detection in images has been widely used in image processing system and computer vision. Morphological edge detection has used structuring elements with fixed shapes. This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with PFOM and ROC curves. The Experiments demonstrate that these novel operators outperform classical morphological operations with a fixed, space-invariant structuring elements for edge detection applications.

• Journal of Environmental Science International
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• v.23 no.9
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• pp.1609-1618
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• 2014

In this study, as a fundamental study for the remediation of the radionuclides-contaminated soil, the adsorption of cobalt, strontium, and cesium on natural soil and kaolin were experimently investigated and adsorption characteristics were evaluated by using several adsorption kinetic and isotherm models. The pseudo-first-order kinetic model (PFOM), pseudo-second-order kinetic model (PSOM), one-site mass transfer model (OSMTM), and two compartment first-order kinetic model (TCFOKM) were used to evaluate the kinetic data and the pseudo-second-order kinetic model was the best with good correlation. The adsorption equilibria of cobalt, strontium, and cesium on natural soil were fitted successfully by Redlich-Peterson and Sips models. For kaolin, the adsorption equilibria of cobalt, strontium, and cesium were fitted well by Redlich-Peterson, Freundlich, and Sips models, respectively. The amount of adsorbed radionuclides on natural soil and kaolin was in the order of cesium > strontium > cobalt. It is considered that these results could be useful to predicting the adsorption behaviors of radionuclides such as cobalt, strontium, and cesium in soil environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.21-31
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• 2017

In this paper, the Zynq system-on-chip (SoC) platform is used to design an adaptive noise reduction and edge-detection system using partial reconfiguration. Filters are implemented in a partially reconfigurable (PR) region to provide high computational complexity in real-time, 1080p video processing. In addition, partial reconfiguration enables better utilization of hardware resources in the embedded system from autonomous replacement of filters in the same PR region. The proposed edge-detection system performs adaptive noise reduction if the noise density level in the incoming video sequences exceeds a given threshold value. Results of implementation show that the proposed system improves the accuracy of edge-detection results (14~20 times in Pratt's Figure of Merit) through self-reconfiguration of filter bitstreams triggered by noise density level in the video sequences. In addition, the ZyCAP controller implemented in this paper enables about 2.1 times faster reconfiguration when compared to a PCAP controller.