Feature analysis-based video flame detecting method

Abstract

The invention discloses a feature analysis-based video flame detecting method. For a video image acquired by a monitoring camera in a fixed visual field. the method comprises the following steps of: firstly, performing binary cutting of the image by maximum between-cluster variance method and acquiring a foreground region; secondly, removing noise points by morphological filtering, and counting a plurality of features of the foreground region, such as colour illumination, geometry, diffusion property, irregularity, sparkling frequency and the like; and finally, comprehensively judging the calculated features of the foreground region to judge whether the video image has flame or not. The binary cutting of the image by maximum between-cluster variance method can reduce the influence of a large amount of disturbances. At the same time, in order to overcome the defect of single or few discriminating features of the currently usually used flame detecting method, the method extracts the plurality of features of the foreground region acquired by the maximum between-cluster variance method to make a comprehensive judgment, so the method realizes quick and accurate judgment that whether the video image has flame or not and greatly reduces false alarm rate.

Description

technical field [0001] The invention belongs to the field of pattern recognition, specifically relates to the technical field of fire monitoring, in particular to a video image pattern recognition method based on feature analysis to detect flame phenomena in the video. Background technique [0002] The prevention and detection of fire has always been the goal pursued by human beings in the process of fighting against fire. For the indoor environment, smoke-sensing, temperature-sensing, and light-sensing detectors can be installed, which use the characteristics of smoke, temperature, and light of fire flames to detect fires. But for a long time, in tall spaces or outdoors, early fire detection has been a difficult problem worldwide. Because in this type of environment, there are many factors that affect fire detection, mainly including: detection method, space height, heat barrier, coverage, air velocity, explosive / toxic gas, acceptable false alarm rate, alarm information ma...

AI Technical Summary

Problems solved by technology

Some existing video flame detection methods, either because of weak anti-interference ability, or because the discriminant features used are relatively simple, make it difficult to avoid false alarms and false alarms, and their adaptability and stability in complex monitoring environments are also not good. satisfactory

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