Ganesan, R. (59577738900) and Somasundaram, K. (57196055256) (2019) Petrol quality analysis for different level of adulteration using thermal imaging and GLCM features.
Full text not available from this repository.Abstract
The most common adulterants in petrol is kerosene. The combination of kerosene and petrol affects the engine working and pollutes the environment as a whole. In this paper, a novel thermal image processing based approach applies to detect the presence of adulteration in fuel. The GLCM (Gray level co-ocurrence matrix) algorithm applies to detect fuel adulterants in a given sample. Test results shows, GLCM algorithm detects adulterants in fuel with 98% accuracy. © 2019 Elsevier B.V., All rights reserved.
| Item Type: | Article |
|---|---|
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 11 Dec 2025 05:59 |
| URI: | https://ir.vmrfdu.edu.in/id/eprint/4674 |
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