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Survey of the Various Techniques Used for Smoke Detection Using Image Processing

  • Shirley SelvanEmail author
  • David Anthony Durand
  • V. Gowtham
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)

Abstract

The concept of smoke detection was put forth by the development of sensors. These sensors relayed the parameters they sensed to a processor which made decisions. The presence of smoke is often an indicator of fire. Hence, given the ability to detect smoke in the early stages of fire, major fire accidents can be prevented. All though this method of smoke detection using sensors was a great success it was not very usefully in extreme conditions (weather, range, location) and sometimes even produced false alarms. Image processing paved way for more accurate detection of smoke since it uses digital data rather than analog inputs. With image processing both, fire and smoke could be detected easily. This method of detection involves various processes like extracting features, comparing with references, classification etc. This survey paper briefly explains the various techniques proposed/used to detect smoke.

Keywords

Stationary wavelet transform Change detection Multi-layer perceptron Support Vector Machine Feret’s region Covariance descriptors Dual dictionary modelling Sparse representation 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Shirley Selvan
    • 1
    Email author
  • David Anthony Durand
    • 1
  • V. Gowtham
    • 1
  1. 1.Department of Electronics and CommunicationSt. Joseph’s College of EngineeringChennaiIndia

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