Dr. Yi-Chang James Tsai, associate professor in the School of Civil and Environmental Engineering at Georgia Tech, is gaining attention for his innovative research to support the development of an intelligent sign asset inventory and management system. Entitled "Using Image Pattern Recognition Algorithms for Processing Video Log Images to Enhance Roadway Infrastructure Data Collection," Tsai's project was awarded funding in 2009 from the Highway Innovations Deserving Exploratory Analysis (IDEA) program. The Highway IDEA program is a project of the National Cooperative Highway Research Program (NCHRP) that seeks proposals with potential to advance the construction, safety, maintenance, and management of highway systems.
Tsai's research pioneered an innovative approach to detect and recognize street and highway signs as a potential way to dramatically reduce the time and effort related to developing sign inventories. His research involves the development of image processing and pattern recognition algorithms, and the preliminary results have established the theoretical and practical foundations to develop a unique system for intelligent inventory management.
This research has tremendous potential to directly benefit U.S. highway agencies by providing a safe and cost-effective means to manage and maintain signage on all roads and highways throughout the country. Even the U.S. Department of Transportation (DOT) has taken notice. In 2010, the DOT awarded Dr. Tsai a national demonstration project for this research initiative after extensive review by transportation experts from across the country. Dr. Tsai's research was featured in the latest issue of Ignition, a periodic news magazine from the National Academies' Transportation Research Board (TRB), Studies and Special Programs Division. A PDF copy of this publication is available on the TRB web site at: http://www.trb.org/Main/Blurbs/Ignition_Magazine_News_from_TRBs_IDEA_Programs_Spr_163652.aspx.
In addition, Tsai's research has potential for other industries alike. In cooperation with the Georgia Logistics Innovation Center (GLIC), Dr. Tsai has extended his research to the development of a maritime awareness system that is currently being used on Elba Island, located five miles downstream from Savannah, Georgia. The purpose of this system is to detect and monitor waterway activities and objects, such as containers, vessels, and even dolphins.
According to Dr. Tsai, “The developed image processing and pattern recognition algorithms play a key role in this initiative. The development of an intelligent sign asset inventory and management system could potentially provide multiple benefits in terms of safety and asset management for a relatively low cost. In fact, the Federal Highway Administration has mandated all transportation agencies in the U.S. to establish a sign condition management method by January, 2012, and one of the biggest challenges in sign asset management is the lack of a comprehensive inventory.
Sign asset data is a critical component of traffic regulation and roadway safety. The data must be timely and easily accessible to transportation agencies. Otherwise, agencies cannot effectively manage inventories or workloads. "With the developed image processing and pattern recognition algorithms, intelligent asset inventory and management systems provide a cost effective way for transportation agencies to inventory traffic signs using the regular roadway images that are widely available and easy to acquire,” states Tsai.
SIGN DETECTION VIDEO:
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For additional information about Dr. James Tsai and his research efforts, visit: http://www.gtsav.gatech.edu/go/faculty/tsai.
