Early-stage smoke detection method based on codebook model and multiple features

Abstract

The invention discloses an early-stage smoke detection method based on a codebook model and multiple features. The method comprises the following steps of: 1, using the codebook model to perform background modeling for a video sequence photographed by a camera, and obtaining a foreground likelihood information image by a background subtraction method; 2, filtering the interference of other objects in the foreground likelihood information image through an improved smoke region color model to get a suspected smoke region in the foreground likelihood information image; 3, further detecting the suspected smoke region by a shape model of a merged smoke region, and filtering an interference region, of which the color is similar to that of the smoke and the shape feature is different from that of the smoke; and 4, further screening the suspected smoke region by a dynamic model of the merged smoke region, and filtering the objects, of which the rate of increase is too low and the smoke region central position moves too fast, in an early-stage smoke region. In the method, the suspected smoke region is screened based on the color feature, the shape model feature and the dynamic feature of the smoke, thus the smoke detection accuracy and the system robustness both are improved.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an early smoke detection method based on a codebook model and multiple features. Background technique [0002] Smoke is the early manifestation of fire. If the smoke in the monitoring scene can be detected accurately and timely, the success rate of fire warning will be greatly improved and the loss will be minimized. [0003] Traditional smoke detection uses sensors to monitor changes in physical quantities such as temperature and gas composition, and then make corresponding judgments. The sensor is limited by air flow, which is not ideal for smoke detection in larger spaces. [0004] Since video surveillance is not limited by spatial distance and scenes, the method of smoke detection based on video has attracted more and more attention from scholars at home and abroad. In an existing implementation based on video analysis, a color feature model based on RGB component operations...

AI Technical Summary

Problems solved by technology

However, the above methods only consider the characteristics of smoke in one aspect, resulting in a high false detection rate in some scenarios.

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