Paper
5 May 2010 A multispectral automatic target recognition application for maritime surveillance, search, and rescue
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Abstract
Due to increased security concerns, the commitment to monitor and maintain security in the maritime environment is increasingly a priority. A country's coast is the most vulnerable area for the incursion of illegal immigrants, terrorists and contraband. This work illustrates the ability of a low-cost, light-weight, multi-spectral, multi-channel imaging system to handle the environment and see under difficult marine conditions. The system and its implemented detecting and tracking technologies should be organic to the maritime homeland security community for search and rescue, fisheries, defense, and law enforcement. It is tailored for airborne and ship based platforms to detect, track and monitor suspected objects (such as semi-submerged targets like marine mammals, vessels in distress, and drug smugglers). In this system, automated detection and tracking technology is used to detect, classify and localize potential threats or objects of interest within the imagery provided by the multi-spectral system. These algorithms process the sensor data in real time, thereby providing immediate feedback when features of interest have been detected. A supervised detection system based on Haar features and Cascade Classifiers is presented and results are provided on real data. The system is shown to be extendable and reusable for a variety of different applications.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jon Schoonmaker, Scott Reed, Yuliya Podobna, Jose Vazquez, and Cynthia Boucher "A multispectral automatic target recognition application for maritime surveillance, search, and rescue", Proc. SPIE 7666, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IX, 76661V (5 May 2010); https://doi.org/10.1117/12.852651
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Cameras

Video

Automatic target recognition

Imaging systems

Target detection

Long wavelength infrared

Detection and tracking algorithms

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