A Review Survey on Smoke Detection

:- The quickly detection of smoke in outer areas using video frame is important task of modern surveillance system.Real video include things that are same to smoke with changing behavior due to low resolution,blurred or weather properties.So we need a detection of smoke in such cases.Since smoke does not have fixed shape. Smoke is also affected from surroundings areas such as lightning affect. Smoke work as indicator for presence of fire. In image processing,images like video frames or pictures are the inputs and output can be an image or image characteristics. Various tasks like classification, features extraction, recognizing different patterns can be performed using image processing. Image processing techniques greatly help to detect smoke/fire in a good manner and thereby avoid dangerous situation according to the output.We will discuss different techniques for detection of smoke

[1]  Nikolaos Grammalidis,et al.  Higher Order Linear Dynamical Systems for Smoke Detection in Video Surveillance Applications , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Zhou Gu,et al.  Early smoke detection of forest fire video using CS Adaboost algorithm , 2015 .

[3]  Simone Calderara,et al.  Vision based smoke detection system using image energy and color information , 2011, Machine Vision and Applications.

[4]  ByoungChul Ko,et al.  Spatiotemporal bag-of-features for early wildfire smoke detection , 2013, Image Vis. Comput..

[5]  Feiniu Yuan,et al.  A fast accumulative motion orientation model based on integral image for video smoke detection , 2008, Pattern Recognit. Lett..

[6]  Nikolaos Grammalidis,et al.  Smoke detection using spatio-temporal analysis, motion modeling and dynamic texture recognition , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

[7]  Teresa A. Vidal-Calleja,et al.  Integrated probabilistic generative model for detecting smoke on visual images , 2012, 2012 IEEE International Conference on Robotics and Automation.

[8]  Payam Saisan,et al.  Dynamic texture recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[9]  Feiniu Yuan,et al.  A double mapping framework for extraction of shape-invariant features based on multi-scale partitions with AdaBoost for video smoke detection , 2012, Pattern Recognit..

[10]  Matti Pietikäinen,et al.  Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Nuno Vasconcelos,et al.  Classifying Video with Kernel Dynamic Textures , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Dmitry Chetverikov,et al.  Dynamic Texture Recognition Using Normal Flow and Texture Regularity , 2005, IbPRIA.

[13]  Wei Yuan,et al.  A Modified Method of Video-based Smoke Detection for Transportation Hub Complex , 2013 .