Publication Type : Conference Paper
Publisher : IEEE
Source : 2019 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 2019, pp. 1777-1781, doi: 10.1109/ICCES45898.2019.9002211.
Url : https://ieeexplore.ieee.org/document/9002211
Campus : Coimbatore
School : School of Engineering
Year : 2019
Abstract : This paper presents the use of hyperspectral image processing as an alternative to traditional mineral exploration techniques for identification of regions in the study area rich in zinc mineral. Zincian Dolomite is a known ore of zinc found in the study area. The Hyperion sensor dataset of a study area in Rajasthan, India is obtained from the USGS (United States Geological Survey) Earth explorer and pre-processed using ENVI (Environment for Visualizing Images) software to remove noise. The pre-processed data is later exported to a dedicated python program which uses machine learning algorithms to identify the regions rich in Zincian Dolomite. The proposed technique form mineral exploration is faster and cheaper than the traditional techniques and is also found to be very accurate in identification of the minerals.
Cite this Research Publication : J. Aravinth, B. Nath, M. Siva Subramanian, R. V. S. S. Bulusu and P. Monish, "Machine learning based Detection of Zinc Mineralization North India using Hyperspectral Image Processing," 2019 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 2019, pp. 1777-1781, doi: 10.1109/ICCES45898.2019.9002211.