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Tugas Akhir Informatika

DETEKSI API PADA VIDEO DENGAN GAUSSIAN MIXTURE MODEL UNTUK DETEKSI GERAKAN DAN SEGMENTASI WARNA API DALAM RUANG WARNA YCBCR

Fire is a disaster that can endanger lives and cause property loss. This study tries to build a model for detecting fire in
video with a digital image processing approach using the Gaussian Mixture Model for motion detection and fire color
segmentation in the YCbCr color space. The model is then tested with metrics for accuracy, precision, recall, and
processing speed. The dataset used is in the form of videos with small, medium, large fire sizes, and videos that only
have fire-like objects. The test results show that the algorithm is able to detect fire when the size of the fire is not too
small or the position of the fire is close enough to the camera. The highest recall that can be achieved by the model is
76.38% when using RGB color rules. The performance during the day is relatively better than at night. Algorithm
processing speed is too slow to be implemented in real-time.

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Informasi Detail
Judul Seri
-
No. Panggil
519.5.Ris.d
Penerbit
Universitas Mataram : Fakultas Teknik Unram.,
Deskripsi Fisik
-
Bahasa
Indonesia
ISBN/ISSN
-
Klasifikasi
519.5
Tipe Isi
other
Tipe Media
computer
Tipe Pembawa
audio disc
Edisi
Edisi 1 Jilid 1
Subjek
DETEKSI API PADA VIDEO
Computer Vision, Color Segmentation , YCbCr, Gauss
Info Detail Spesifik
DETEKSI API PADA VIDEO DENGAN GAUSSIAN MIXTURE MODEL UNTUK DETEKSI GERAKAN DAN SEGMENTASI WARNA API DALAM RUANG WARNA YCBCR
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