Petrol quality analysis for different level of adulteration using thermal imaging and GLCM features

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
Subjects: Engineering > Industrial and Manufacturing Engineering
Divisions: Arts and Science > School of Arts and Science, Chennai > Computer Science
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 11 Dec 2025 05:59
URI: https://vmuir.mosys.org/id/eprint/4674

Actions (login required)

View Item
View Item