KEYWORDS: Sensors, Video, Data processing, Cameras, Filtering (signal processing), Roads, Image processing, Detection and tracking algorithms, Signal processing, Video surveillance
This paper describes how optical sensor signal processing and data association methods that have been developed for Aerospace applications can be applied to the traffic monitoring function of Advanced Traffic Management Systems (ATMS). It first discusses techniques that have been developed for background estimation and detection of vehicles on a roadway. Then, the transformation to tracking coordinates and the multiple target tracking (MTT) algorithm that produces traffic flow observation data are outlined. An extended Kalman filter that takes observed flow data from multiple sensor sites and produces flow estimates for an entire roadway is described and its application to incident detection discussed. Preliminary results using simulated and actual freeway data are presented. Finally, techniques for presenting this data to the user and the manner in which these signal and data processing techniques relate to an overall ATMS design are outlined.
A confocal image understanding system was developed which uses the blackboard model of problem solving to achieve computerized identification and characterization of confocal fluorescent images (serial optical sections). The system is capable of identifying a large percentage of structures (e.g., cell nucleus) in the presence of background noise and nonspecific staining of cellular structures. The blackboard architecture provides a convenient framework within which a combination of image processing techniques can be applied to successively refine the input image. The system is organized to find the surfaces of highly visible structures first, using simple image processing techniques, and then to adjust and fill in the missing areas of these object surfaces using external knowledge, and a number of more complex image processing techniques when necessary. As a result, the image analysis system is capable of obtaining morphometrical parameters such as surface area, volume and position of structures of interest automatically. In addition, the system is also used in the characterization of inertial fusion targets where the actual target geometry was checked against ideal parameters. The system provides a powerful tool in the fields of material science and biological research such as micro-structural characterization, morphogenesis, cell differentiation, tissue organization and embryo development.
Conference Committee Involvement (5)
Acquisition, Tracking, Pointing, and Laser Systems Technologies XXVI
23 April 2012 | Baltimore, Maryland, United States
Acquisition, Tracking, Pointing, and Laser Systems Technologies XXV
25 April 2011 | Orlando, Florida, United States
Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV
5 April 2010 | Orlando, Florida, United States
Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIII
14 April 2009 | Orlando, Florida, United States
Acquisition, Tracking, Pointing, and Laser Systems Technologies XXII
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