Smoke Detection Using Texture and Color Analysis in Videos
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
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).
Açıklama
2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEY
Anahtar Kelimeler
Smoke Detection, Wildfire, GLCM, SVM, YUV
Kaynak
2017 International Artificial Intelligence and Data Processing Symposium (Idap)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
