Researches On Forest Smoke Surveillance System Based On DM642 And Image Analysis

It is of great significance to take a research and develop a system of video image analysis for early warning of forest fires and reduce the loss of forest resources based on embedded technology. Because of its small volume and fully functional, the embedded system taking DSP as the core are adopted .Combining with the technology of image processing in machine vision field, it's also becoming a good choice for the forest fire monitoring system. The paper developed the fire smoke detection system based on TMS320DM642 made by TI, took DM642 as the core kernel, and planned the RF5 software framework by DSP/BIOS to complete the multitasking real-time scheduling by the support of the projects of major science and technology in Zhejiang -- solar energy-based forest fire monitoring technology and system development.Smoke is a remarkable characteristic for early forest fire, the timely detection of smoke is an effective approach to improve the ability of fire warning. According to actual application requirements of smoke detection in the open environment, an on- line algorithm based on multi-feature integration and neural network or Support Vector Machine (SVM) was proposed. Firstly, a smoke-color model adapted to open environment and resistance to light was presented, then, got the suspected smoke area with Kalman motion detection by image fusion. Secondly, four spatial characteristics of smoke were extracted as follows: contour irregularities, area of avian, ambiguity of smoke region, low frequency oscillation of smoke use wavelet and so on, as the inputs of BP neural network and support vector machine trained completed offline. Finally, the paper used the classifier's outputs to determine whether there was occurring fires.The debugging and experiments'results show that the system is reliable and higher effective, the design of system and resource allocations are correctly reasonable. The algorithm of paper can realize real-time video smoke detection under certain conditions, and adapts to the open environment, meets the requirements of fire smoke warning in open environment and desired effects.