Journal of Multimedia Information System

Korea Multimedia Society (한국멀티미디어학회)
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Smoke Detection System Research using Fully Connected Method based on Adaboost

  • Lee, Yeunghak (Computer Engineering, Andong National Univ.) ;
  • Kim, Taesun (Dept. of Avionics Eng. College of Aviation, Kyungwoon University) ;
  • Shim, Jaechang (Computer Engineering, Andong National Univ.)
  • Received : 2017.06.28
  • Accepted : 2017.06.29
  • Published : 2017.06.30
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Abstract

Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.

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References

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