The ash fall-out following explosion activity of volcanoes represents serious hazard for both road and air traffic. In this paper the development of a low-cost vision system for the monitoring of ash fall-out phenomena by measuring ash granulometry is reported. The proposed methodology is based on a suitable image processing paradigm that has been implemented in Python/Open CV on an embedded, single board computer architecture, Raspberry Pi 4 Model B and a Pi Camera module v2.1. The design and realization of a prototype are reported. Experimental investigations have been performed using reference images.
An embedded vision tool for volcanic ash analysis
Ando' B.;Baglio S.;Castorina S.;Graziani S.;Marletta V.;Trigona C.
2021-01-01
Abstract
The ash fall-out following explosion activity of volcanoes represents serious hazard for both road and air traffic. In this paper the development of a low-cost vision system for the monitoring of ash fall-out phenomena by measuring ash granulometry is reported. The proposed methodology is based on a suitable image processing paradigm that has been implemented in Python/Open CV on an embedded, single board computer architecture, Raspberry Pi 4 Model B and a Pi Camera module v2.1. The design and realization of a prototype are reported. Experimental investigations have been performed using reference images.File in questo prodotto:
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