IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Reducing False Alarms in Vision-Based Fire Detection

Reducing False Alarms in Vision-Based Fire Detection
View Sample PDF
Author(s): Neethidevan Veerapathiran (Mepco Schlenk Engineering College, India)and Anand S. (Mepco Schlenk Engineering College, India)
Copyright: 2017
Pages: 28
Source title: Applied Video Processing in Surveillance and Monitoring Systems
Source Author(s)/Editor(s): Nilanjan Dey (Techno India College of Technology, Kolkata, India), Amira Ashour (Tanta University, Egypt)and Suvojit Acharjee (National Institute of Technology Agartala, India)
DOI: 10.4018/978-1-5225-1022-2.ch012

Purchase

View Reducing False Alarms in Vision-Based Fire Detection on the publisher's website for pricing and purchasing information.

Abstract

Computer vision techniques are mainly used now a days to detect the fire. There are also many challenges in trying whether the region detected as fire is actually a fire this is perhaps mainly because the color of fire can range from red yellow to almost white. So fire region cannot be detected only by a single feature and many other features (i.e.) color have to be taken into consideration. Early warning and instantaneous responses are the preventing ideas to avoid losses affecting environment as well as human causalities. Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms. In order to reduce false alarms of conventional fire detection systems, system make use of vision based fire detection system. This chapter discuss about the fundamentals of videos, various issues in processing video signals, various algorithms for video processing using vision techniques.

Related Content

Aswathy Ravikumar, Harini Sriraman. © 2023. 18 pages.
Ezhilarasie R., Aishwarya N., Subramani V., Umamakeswari A.. © 2023. 10 pages.
Sangeetha J.. © 2023. 13 pages.
Manivannan Doraipandian, Sriram J., Yathishan D., Palanivel S.. © 2023. 14 pages.
T. Kavitha, Malini S., Senbagavalli G.. © 2023. 36 pages.
Uma K. V., Aakash V., Deisy C.. © 2023. 23 pages.
Alageswaran Ramaiah, Arun K. S., Yathishan D., Sriram J., Palanivel S.. © 2023. 17 pages.
Body Bottom