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Computer Optics, 2018, Volume 42, Issue 1, Pages 128–140 (Mi co487)  

IMAGE PROCESSING, PATTERN RECOGNITION

Images analysis for automatic volcano visibility estimation

A. N. Kamaev, I. P. Urmanov, A. A. Sorokin, D. A. Karmanov, S. P. Korolev

Computing Center FEB RAS, Khabarovsk, Russia

Abstract: In this paper, a method for estimating the volcano visibility in the images is presented.This method includes algorithms for analyzing parametric edges of objects under observation and frequency characteristics of the images. Procedures for constructing parametric edges of a volcano and their comparison are considered. An algorithm is proposed for identifying the most persistent edges for a group of several reference images. The visibility of a volcano is estimated by comparing these edges to those of the image under analysis. The visibility estimation is maximized with respect to a planar shift and rotation of the camera to eliminate their influence on the estimation. If the image quality is low, making it hardly suitable for further visibility analysis, the estimation is corrected using an algorithm for analyzing the image frequency response represented as a vector of the octave frequency contribution to the image luminance. A comparison of the reference frequency characteristics and the characteristics of the analyzed image allows us to estimate the contribution of different frequencies to the formation of volcano images. We discuss results of the verification of the proposed algorithms performed using the archive of a video observation system of Kamchatka volcanoes. The estimates obtained corroborate the effectiveness of the proposed methods, enabling the non-informative imagery to be automatically filtered off while monitoring the volcanic activity.

Keywords: image analysis, algorithms, edge detection, parametric edges, volcano, edge matching, video surveillance, visibility analysis.

Funding Agency Grant Number
Russian Foundation for Basic Research 16-07-00156
16-37-00026 _
Far Eastern Branch of the Russian Academy of Sciences 15-I-4-071
15-I-4-072
The work was partially funded by the Russian Foundation for Basic Research (RFBR) under research projects # 16-07-00156 and 16-37-00026 mol_a, and a Complex Fundamental Research Program of the Far Eastern Branch of the Russian Academy of Sciences "Far East" (projects ##15-I-4-071, 15-I-4-072).


DOI: https://doi.org/10.18287/2412-6179-2018-42-1-128-140

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Full text: http://www.computeroptics.smr.ru/.../420116.html
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Received: 26.05.2017
Accepted:09.07.2017

Citation: A. N. Kamaev, I. P. Urmanov, A. A. Sorokin, D. A. Karmanov, S. P. Korolev, “Images analysis for automatic volcano visibility estimation”, Computer Optics, 42:1 (2018), 128–140

Citation in format AMSBIB
\Bibitem{KamUrmSor18}
\by A.~N.~Kamaev, I.~P.~Urmanov, A.~A.~Sorokin, D.~A.~Karmanov, S.~P.~Korolev
\paper Images analysis for automatic volcano visibility estimation
\jour Computer Optics
\yr 2018
\vol 42
\issue 1
\pages 128--140
\mathnet{http://mi.mathnet.ru/co487}
\crossref{https://doi.org/10.18287/2412-6179-2018-42-1-128-140}


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