Smoke Detection Using Texture and Color Analysis in Videos

TOPTAŞ M., HANBAY D.

2017 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Türkiye, 16 - 17 Eylül 2017 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/idap.2017.8090321
  • Basıldığı Şehir: Malatya
  • Basıldığı Ülke: Türkiye
  • İnönü Üniversitesi Adresli: Evet

Özet

The delays in the detection of fire in fire detection systems continue to be a life threatening problem for living things. Techniques based on image processing have been developed in order to remove this problem and minimize the detection period. This study also focused on the smoke image that appeared before the flame at the time of the fire. Smoke detection can provide earlier notification than flame detection. In the first step of the proposed method, smoke zone was detected with YUV color space. After than the Gray Level Co-Occurrence Matrix (GLCM) was used to extract the features that represent the smoke images. At last, these features are used to classify the smoke and non-smoke space by using Support Vector Machines (SVM).