Integrated mobile systems using image analysis with applications in public safety
One of the roles of emergency first responders (e.g. police and fire departments) is to prevent and protect against events that can jeopardize the safety and well being of a community. Examples include criminal gang activity and the handling and transportation of dangerous materials. In each of these cases first responders need tools for finding, documenting, and taking the necessary actions to mitigate the problem or issue. The goal of this thesis is to develop integrated mobile-based systems capable of using location-based-services, combined with image analysis, to provide accurate and useful information to the first responders in real time. Two systems have been developed. The first is a system to track and analyze gang activity through the acquisition, indexing and recognition of gang graffiti images. This approach uses image analysis methods for color correction, color recognition, image segmentation, and image retrieval and classification. A database of gang graffiti images is described that includes not only the images but also metadata related to the images, such as date and time, geoposition, gang, gang member, colors, and symbols. The user can then query the data in a useful manner. The second is a system that can recognize and interpret hazardous material (hazmat) signs typically displayed by vehicles transporting dangerous materials. This approach uses image analysis methods for hazmat sign interpretation, including shape location detection and color recognition. The detection results are used to query an electronic version of the Emergency Response Guidebook (ERG) and return information and advice to help first responders. A database of hazmat sign and scene images for forensic analysis is described that includes images and metadata.
Delp, Purdue University.
Computer Engineering|Electrical engineering
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