Fire Detection Based On Image Processing

Forest fire is an important natural calamities in over the world and is regarded highly by many countries in the world,since forest fire have such features as spreading speed quickly difficulty of extinguishing a fire and rescuing human beings and properties,so it has been an increasing urgent demand that how to effectively protect the safety of high building and detect the fire as early as possible.As a new-style and effective measure for the detection of early fire,much attention has been focused on image fire detection technology.This paper interoduced the basic theory that the colour image processing and color space relevance knowledge,the colour fire image with obvious colour characteristic was put a important position to study,discuss and analysis from two aspects that colour space and segmentation method.The first colour space which appear for many years in colour image division field has carried out induction and the summary,has point out all kind of characteristic of colour space in colour image cut.Finally,according to the characteristic carving up problem choose proper division method and right color space,design the colour fire image division method in YCrCb model and then use the similar distance method in HLS space to advance the processing effect.On the basis of studying above,classify the collecting fire image and take BP neural networks as carrier and use the fire image characteristic to identify.the features such as color,texture and shape variety of fire flame and other disturbing phenomena have been detailed studied in this dissertation.And the corresponding recognition algorithms have been given.So the early fire flame can be recognized and the disturbing phenomena can be distinguished.The fire detecting scheme based on nerve net has been discussed in the last part of this dissertation.First,the basic concept of nerve net has been introduced.And then the detail structure of the BP nerve net and the detail design precept of input and output layer have been given.The experiment results show that the BPNN fire detection system has good anti-interference capability.