Feature Selection for Intelligent Firefighting Robot Classification of Fire, Smoke, and Thermal Reflections Using Thermal Infrared Images

Kim, Jong-Hwan; Jo, Seongsik; Lattimer, Brian Y.

Feature Selection for Intelligent Firefighting Robot Classification of Fire, Smoke, and Thermal Reflections Using Thermal Infrared Images

dc.contributor.author	Kim, Jong-Hwan	en
dc.contributor.author	Jo, Seongsik	en
dc.contributor.author	Lattimer, Brian Y.	en
dc.contributor.department	Mechanical Engineering	en
dc.date.accessioned	2017-09-18T09:35:02Z	en
dc.date.available	2017-09-18T09:35:02Z	en
dc.date.issued	2016-09-20	en
dc.date.updated	2017-09-18T09:35:02Z	en
dc.description.abstract	Locating a fire inside of a structure that is not in the direct field of view of the robot has been researched for intelligent firefighting robots. By classifying fire, smoke, and their thermal reflections, firefighting robots can assess local conditions, decide a proper heading, and autonomously navigate toward a fire. Long-wavelength infrared camera images were used to capture the scene due to the camera’s ability to image through zero visibility smoke. This paper analyzes motion and statistical texture features acquired from thermal images to discover the suitable features for accurate classification. Bayesian classifier is implemented to probabilistically classify multiple classes, and a multiobjective genetic algorithm optimization is performed to investigate the appropriate combination of the features that have the lowest errors and the highest performance. The distributions of multiple feature combinations that have 6.70% or less error were analyzed and the best solution for the classification of fire and smoke was identified.	en
dc.description.version	Published version	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Jong-Hwan Kim, Seongsik Jo, and Brian Y. Lattimer, “Feature Selection for Intelligent Firefighting Robot Classification of Fire, Smoke, and Thermal Reflections Using Thermal Infrared Images,” Journal of Sensors, vol. 2016, Article ID 8410731, 13 pages, 2016. doi:10.1155/2016/8410731	en
dc.identifier.doi	https://doi.org/10.1155/2016/8410731	en
dc.identifier.uri	http://hdl.handle.net/10919/78930	en
dc.language.iso	en	en
dc.publisher	Hindawi	en
dc.rights	Creative Commons Attribution 4.0 International	en
dc.rights.holder	Copyright © 2016 Jong-Hwan Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.	en
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	en
dc.title	Feature Selection for Intelligent Firefighting Robot Classification of Fire, Smoke, and Thermal Reflections Using Thermal Infrared Images	en
dc.title.serial	Journal of Sensors	en
dc.type	Article - Refereed	en
dc.type.dcmitype	Text	en