Developing volcano image analysis algorithms to monitor dangerous natural phenomena

Abstract

Relevance. Video surveillance systems are the most important type of instrumental means of observing the state of volcanoes. The high intensity of data collection contributes to the formation of a huge array of images. At the same time climatic peculiarities of the investigated objects location as well as not always stable operation of data transmission channels cause a large number of spoiled or uninformative images. Additional time is spent on viewing them and excluding them from the archive by specialists, which, in general, may affect the speed of decision-making, related to informing the interested parties about the occurrence of natural hazards. In this regard, the task of developing methods and technologies of image analysis and filtering for creating an effective system of video surveillance of volcanoes is relevant. The aim of the research is to develop the algorithms for image analysis of volcanoes. Methods: Canny boundary detector, discrete contours transformation into parametric ones in the form of broken lines, calculation of reference characteristics and comparison of the obtained data with them, analysis of frequency characteristics of the image using Haar transformation, decomposition of the image into a multiscale pyramid, drawing up a vector of characteristic visual features of an object, detection of the object being searched for using an SVM-classifier. Results: Algorithms of photo analysis to assess the visibility of volcanoes and search for brightness anomalies. Conclusion. The considered study resulted in developing volcano image analysis algorithms. The methods and approaches used make it possible to effectively solve the problem of assessing the visibility of an object and searching for brightness anomalies. The system capabilities provide a sufficient set of tools to effectively solve the problem of image filtering and searching for brightness anomalies as a possible sign of a volcano's activity. The results obtained can be used in volcano activity monitoring systems to ensure aviation safety and population protection.