A Novel Python Program to Automate Soil Colour Analysis and Interpret Surface Moisture Content

Vinay Kumar Gadi1, Dastan Alybaev2, Priyanshu Raj1, Akhil Garg3, Guoxiong Mei4, Sekharan Sreedeep1, Lingaraj Sahoo5
1Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, India
2Department of Computer Science and Engineering, American University of Central Asia, Bishkek, Kyrgyzstan
3Division of Computational Mathematics and Engineering, and Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh city, Vietnam
4Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education, College of Civil Engineering and Architecture, Guangxi University, Nanning, China
5Department of Biosciences and Bioengineering Engineering, Indian Institute of Technology Guwahati, Guwahati, India

Tóm tắt

Most of the previous researchers used manual image processing approach through a public domain tool (ImageJ) to interpret soil surface moisture content. However, the manual processing could not be possible, when the number of images is significantly large. In addition, results could not be reproduced with conventional manual image processing. This technical note introduces a novel technique to automate the quantification process of soil surface moisture content. A stepwise strategy was demonstrated to remove user dependency for soil colour analysis using an autonomous Python script. The images of the compacted soil were captured using a commercially available camera model. The image analysis was conducted using conventional manual image processing approach and newly developed technique. The difference between the mean gray values obtained from the above mentioned two approaches was very low (< 3%). Hence, the newly developed technique is cost-effective and feasible for programming with drones to monitor soil surface moisture content in large areas.

Tài liệu tham khảo

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