Color ImageBased Defect Detection Method for Bridge Coating Assessment

This paper presents a highly efficient method for recognizing the existence of bridge coating rust defects by using color image processing. The detection of defects on steel bridge surfaces during the operation and maintenance of bridge structures is important to ensure the safety and reliability of them. More advanced techniques such as digital image processing have been studied for better monitoring and detection as existing infrastructure systems are aged and deteriorated rapidly. Recently, image-based defect recognition and assessment methods have gained considerable attention in the civil engineering domain due to their accuracy, speed, and lower cost. The proposed method in this paper is a fast decision-making system by utilizing color image processing. It was developed by processing original bridge coating images to generate color values and calculating eigenvalues from each digitized image. The values from two different groups, a defective group and a nondefective group, are compared each other to figure out the feasibility of this approach. Finally, an automated defect recognition method is presented and tested with more images. This method can be used to make a decision whether a given digitized image contains defects.

Areas vulnerable to natural disasters and damage estimation of infrastructure in Busan, Korea

Since the damages caused by disasters associated with climate anomalies and the diversification of the social structure increase every year, an efficient management system associated with a damage assessment of the areas vulnerable to disasters is demanded to prevent or mitigate the damages to infrastructure. The areas vulnerable to disasters in Busan, located at southeastern part of Korea, were estimated based on historical records of damages and a risk assessment of the infrastructure was performed to provide fundamental information prior to the establishment of the real-time monitoring system for infrastructure and establish disaster management system. The results are illustrated by using geographical information system(GIS) and provide the importance of the roadmap for comprehensive and specific strategy to manage natural disasters.

The Use of Life Cycle Management Principles in Biosystems Engineering： A Pragmatic Approach to Solving Agri-industrial Sustainability Problems

LCM （life cycle management） is a systematic approach, mindset and culture that considers economic, social, and environmental factors among other factors in the decision making process throughout various business or organizational decisions that affect both inputs and outputs of a product or service life cycle. It is a product, process, or activity management system aimed at minimizing environmental and socio-economic burdens associated with an organization＇s product or process during its entire life cycle and value chain. LCM＇s application is gaining wider acceptance both in the corporate and governmental organizations as an approach to reduce ecological footprints and to improve the sustainability of human activities. But where and how can it be used in agricultural engineering applications？ This study highlights the potential areas of LCM application in agricultural and allied sectors and how it can be utilized. The study revealed that LCM tools such as design for environment and life cycle analysis can be used to evaluate the environmental impacts of-and to improve the products, equipment, and structures produced by biosystems engineers as well as the processes used to generate them.

Imagery Enhancement and Interpretation for Remote Visual Inspection of Aging Civil Infrastructure

In this paper, we describe an image enhancement and interpretation methodology to enhance and recognize surface defects and critical patterns from remote imagery of sewer pipeline inspection. The objective is to provide inspectors and professionals with better tools to allow them to examine the imagery for condition assessment. We present initial results of a collaboration with a robotic company through a case study on computer-assisted processing and interpretation of sewer pipeline inspection imagery. In the mean time, the described enhancement and interpretation methodology can also be applied to sewer pipeline condition assessment in an offline mode, where this methodology can support professionals’ examination of acquired sewer condition imagery.