Habiboğlu, Yusuf Hakan2016-01-082016-01-082010http://hdl.handle.net/11693/15131Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 49-51.In this thesis, automatic fire detection methods are studied in color domain, spatial domain and temporal domain. We first investigated fire and flame colors of pixels. Chromatic Model, Fisher’s linear discriminant, Gaussian mixture color model and artificial neural networks are implemented and tested for flame color modeling. For images a system that extracts patches and classifies them using textural features is proposed. Performance of this system is given according to different thresholds and different features. A real-time detection system that uses information in color, spatial and temporal domains is proposed for videos. This system, which is develop by modifying previously implemented systems, divides video into spatiotemporal blocks and uses features extracted from these blocks to detect fire.ix, 51 leaves, illustrationsEnglishinfo:eu-repo/semantics/openAccessFisher’s linear discriminantGabor filterscodifference descriptorscovariance descriptorsartificial neural networksTA1637 .H33 2010Image processing--Digital techniques.Computer vision.Video compression.Visual texture recognition.Color.Fire detectors.Automatic control.Neural networks (Computer science)Artificial intelligence.Thesis