A Daytime Smoke Detection Method Based on Variances of Optical Flow and Characteristics of HSV Color on Footage from Outdoor Camera in Urban City

In order for detection of a fire in fields, it is effective to detect smoke since it often behaves as a precursor of the fire. One preferable way for early detection is to use visual information from outdoor cameras that widely monitor the filed. There have been many attempts to detect smokes via optical sensors on digital cameras using optical flow methods, but not fully successful from practical-use aspects. It is because the area of smokes occupying on the footage by outdoor cameras is not necessarily large enough. Moreover, in case of urban cities, discrimination of the smokes from other moving objects such as cars, trees and turbines is not easy. Herein we propose a novel method to detect daytime smokes based on variance of optical flow and characteristics of HSV (hue-saturation-value) color. We apply the method to a set of footage of three days obtained in an industrial zone in Japan. Successful results are obtained as over 90% of smokes are detected. Notable is that this method is independent of solar radiation conditions on sunny and cloudy days.