• International conference on construction engineering and project management
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• 2009.05a
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• pp.224-229
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• 2009

Digital image recognition has been used for steel bridge surface assessment since late 1990s. However, the non-uniform illumination problems such as shades, shadows, and highlights are still challenges in image processing to date. Therefore, this paper develops a new approach to tackle the non-uniform illumination problem for rust image adjustment. The inhomogeneous illumination problem is divided into shades/shadows and highlights in this paper. The proposed BEMD-morphology approach (BMA) utilizes the bidimensional empirical mode decomposition to mitigate the shade/shadow effect, and the morphological processing to detect and replace the highlight area. Finally, the rust image processed with the BMA will be segmented by the K-Means algorithm, one of the most popular and effective methods, to show the effectiveness of illumination adjustment.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.449-456
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• 2009

Image processing has been applied to steel bridge defect recognition since 1990s. Compare to human visual inspection, image processing provides a more objective and accurate way of assessment. Since shade and shadow may sometimes occur when taking bridge coating images, non-uniform illumination problems should be considered. By means of color image processing, this paper aims to mitigate the illumination effect for bridge coating assessment. Furthermore, the adaptable ellipse method (AEM) is proposed to recognize mild rust colors. Finally, AEM will be compared to the K-Means algorithm, a popular recognition method, to show its advantage.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.310-313
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• 2024

Rust has gained recognition for its emphasis on and commitment to providing memory safety. However, seamlessly integrating it with Foreign Function Interfaces (FFIs) written in unsafe languages remains a significant challenge towards achieving complete memory safety. To address this challenge, researchers have proposed Foreign Function Isolation as a potential solution, leading to emergence of various approaches in this domain. This paper critically evaluates existing solutions and illuminates the gaps that need to be addressed to realize practical foreign function isolation in Rust.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.257-262
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• 2009

Image processing has been utilized for assessment of infrastructure surface coating conditions for years. However, there is no robust method to overcome the non-uniform illumination problem to date. Therefore, this paper aims to deal with non-uniform illumination problems for bridge coating assessment and to achieve automated rust intensity recognition. This paper starts with selection of the best color configuration for non-uniformly illuminated rust image segmentation. The adaptive-network-based fuzzy inference system (ANFIS) is adopted as the framework to develop the new model, the box-and-ellipse-based neuro-fuzzy approach (BENFA). Finally, the performance of BENFA is compared to the Fuzzy C-Means (FCM) method, which is often used in image recognition, to show the advantage and robustness of BENFA.

• Fashion & Textile Research Journal
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• v.15 no.2
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• pp.219-230
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• 2013

To generate future profits, luxury brands need to recognize and understand customers as individually important and analyze the impact factors that improve specific customer equity. With the growing recognition that customer equity is a key strategic asset, this study empirically investigates the effect of customer equity drivers on customer loyalty based on the study of Vogel et al.(2008) which expanded the Rust et al.(2000)'s study on customer equity. We empirically examine if the customer equity drivers have a different impact on customer loyalty. This study hypothesizes that the relative effect of customer equity drivers would be different depending on the purchasing behavior of consumers and examines the effects of them on the relationship of the drivers of customer equity and customer loyalty. We use stepwise multiple regression analysis to empirically test the relationship of value equity, brand equity, and relationship equity and customer loyalty. Relationship equity influences customer loyalty more strongly than value equity and brand equity. Customers seem to build loyalty based on the careful assessment of all costumer equity drivers (value equity, brand equity, and relationship equity). In addition, their relative impact is different depending on the purchasing behavior of consumers. A company cannot maintain all customer equity drivers at a high level with limited marketing resources; therefore, marketing investment for all customer equity drivers need to be allocated differentially depending on the purchasing behavior of consumers.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.383-389
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• 2016

In this paper, we present the hull blasting machine with vision-based weld bead recognition device for cleaning shipment exterior wall. The purpose of this study is to introduce the mechanism design of the high efficiency hull blasting machine using the vision system to recognize the weld bead. Therefore, we have developed a robot mechanism and drive controller system of the hull blasting robot. And hull blasting characteristics such as the climbing mechanism, vision system, remote controller and CAN have been discussed and compared with the experimental data. The hull blasting robots are able to remove rust or paint at anchor, so the re-docking is unnecessary. Therefore, this can save time and cost of undergoing re-docking process and build more vessels instead. The robot uses sensors to navigate safely around the hull and has a filter system to collect the fouling removed. We have completed a pilot test of the robot and demonstrated the drive control and CAN communication performance.