摘要： In this paper, we propose an automatic image based smoke detection using source separation. In particular, we assume that the region of interest (smoke region) is a linear combination of smoke and background pixels, and we estimate the smoke component. More specifically, we extend the linear hyperspectral unmixing techniques to the context of image based smoke detection in order to separate the smoke component from the background. The proposed approach yields promising results especially with smoke images captured outdoor.
Abstract：In this paper, we propose an automatic image based smoke detection using source separation. In particular, we assume that the region of interest (smoke region) is a linear combination of smoke and background pixels, and we estimate the smoke component. More specifically, we extend the linear hyperspectral unmixing techniques to the context of image based smoke detection in order to separate the smoke component from the background. The proposed approach yields promising results especially with smoke images captured outdoor.
[1] Toreyin B U, Dedeoglu Y, Cetin A E. Wavelet Based Real-Time Smoke Detection in Video. in European Signal Processing Conference, 2005. 4.
[2] Tian H, Li W, Nguyen D T, et al. Smoke Detection in Videos Using Non-Redundant Local Binary Pattern-Based Features. in Multimedia Signal Processing (MMSP), 2011 IEEE 13th International Workshop on, 2011. 1.
[3] Levin A，Weiss Y. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2007，29：1647.
[4] Bell A J，Sejnowski T J. Blind Separation and Blind Deconvolution: an Information-Theoretic Approach. in Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on, 1995. 3415.
[5] Farid H，Adelson E H. Separating Reflections and Lighting Using Independent Components Analysis. in Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., 1999.
[6] Funaro M, Oja E, Valpola H. Neural Networks, 2003，16：469.
[7] Zhang C，Sato I. Separating Reflective and Fluorescent Components of an Image. in Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, 2011. 185.
[8] Meyer F G, Averbuch A Z, Coifman R R. Image Processing, IEEE Transactions on, 2002，11：1072.
[9] Osher S, Solé A, Vese L. Multiscale Modeling & Simulation, 2003，1：349.
[10] Starck J L, Elad M, Donoho D L. Image Processing, IEEE Transactions on, 2005，14：1570.
[11] Tian H, Li W, Wang L, et al. International Journal of Computer Vision, 2014，106：192.
[12] Tonazzini A, Bedini L, Salerno E. Image Processing, IEEE Transactions on, 2006，15：473.
[13] Sorenson H W，Alspach D L. Automatica, 1971，7：465.
[14] Moon T K. Signal Processing Magazine, IEEE, 1996，13：47.
[15] Guo L，Garland M. Pattern Recognition, 2006，39：1066.
[16] Guidara R, Hosseini S, Deville Y. Image Processing, IEEE Transactions on, 2009，18：2435.
[17] Fadili M J, Starck J L, Bobin J, et al. Proceedings of the IEEE, 2010，98：983.
[18] Szeliski R, Avidan S, Anandan P. Layer Extraction from Multiple Images Containing Reflections and Transparency. in Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on, 2000. 246.
[19] Schechner Y Y, Kiryati N, Basri R. International Journal of Computer Vision, 2000，39：25.
[20] Levin A, Zomet A, Weiss Y. Separating Reflections from a Single Image Using Local Features. in Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, 2004, I-306.
[21] Sarel B，Irani M. Separating Transparent Layers of Repetitive Dynamic Behaviors. in Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on, 2005. 26.
[22] Gai K, Shi Z, Zhang C. Blindly Separating Mixtures of Multiple Layers with Spatial Shifts. in Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, 2008. 1.
[23] Kong N, Tai Y W, Shin S Y. Image Processing, IEEE Transactions on, 2011，20：3393.
[24] Wold S, Esbensen K，Geladi P. Chemometrics and Intelligent Laboratory Systems, 1987，2：37.
[25] Wright J, Ma Y, Mairal J, et al. Proceedings of the IEEE, 2010, 98: 1031.
[26] Long F, Zhang H, Feng D D. Fundamentals of Content-Based Image Retrieval. in Multimedia Information Retrieval and Management, ed: Springer, 2003. 1.
[27] Pietikinen M. Image Analysis with Local Binary Patterns. in Image Analysis, ed: Springer, 2005. 115.
[28] Bchir O, Ismail M M B, Frigui H. Mixture Analysis based on Spectral Summarization. IEEE WHISPERS Gainsville, Florida., 2013.
[29] Berman M, Kiiveri H, Lagerstrom R, et al. IEEE transactions on Geoscience and Remote Sensing, 2004，42：2085.
[30] Zare A，Gader P. IEEE Geoscience and Remote Sensing Letters, 2007，4：446.
[31] Bezdek J C, Ehrlich R, Full W. Computers & Geosciences, 1984，10：191.
[32] http://www.globalmusicdepot.com/find/mp3/song/asl-vision-video-smoke-detection-demo-manufacturing-area.aspx.
[33] www.youtube.com/watch?v=WOdnleMs3Rk.
[34] https://www.youtube.com/watch?v=uSwOyGHeDkM.
[35] https://www.youtube.com/watch?v=6_j7BKioi3M.
[36] Bchir O，Ben Ismail M M. Intelligent Automation & Soft Computing, 2015. 1.
[37] Smits B. Journal of Graphics Tools, 1999，4：11.
