BibTeX:

@article{IJIRSTV5I10006,
     title={Advanced Smoke Recognition of Forest Wildfire using PCA Algorithm},
     author={Ms. J. Maheswari, Ms. Divya Roshini, Ms. Indhuja and Ms. Kirithika N},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={5},
     number={10},
     pages={40--42},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV5I10006.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

This research uses Machine learning (image mining techniques) for detecting smoke through an image or frame using difference in luminance and chrominance of the red and blue color. The smoke generated usually has peculiar color which can be used for it to be differentiated between a fog and smoke. This paper uses the color model and principal component analysis to effectively differentiate between smoke and other background objects. The methods used for color modeling is YCbCr and the algorithm proposed. This article considers an image as linear blending of smoke component and background component. Under this assumption this paper discusses a model and its solution using the concept of PCA.

Machine learning, YCbCr, PCA, Data set, Feature Extraction