Versatile image processing technique for fuel science: A review
| Autor: | Michael Rahul Soosai, I. Ganesh Moorthy, Sankar Karthikumar, Arivalagan Pugazhendhi, R. Shyam Kumar, Y. Camy Joshya, Nguyen Thuy Lan Chi |
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| Rok vydání: | 2021 |
| Předmět: |
Biodiesel
Hardware_MEMORYSTRUCTURES Environmental Engineering 010504 meteorology & atmospheric sciences business.industry Computer science Process (computing) Biomass Image processing 010501 environmental sciences Fuel injection 01 natural sciences Pollution Automation Biofuel Digital image processing Environmental Chemistry business Process engineering Waste Management and Disposal 0105 earth and related environmental sciences |
| Zdroj: | The Science of the total environment. 780 |
| ISSN: | 1879-1026 |
| Popis: | The evolution of computer vision and image processing system paved the way that any technologists can extract quantitative data sets from the visual results of an image. Digital image processing (DIP) technique precisely measures and quantifies the image and eliminates the subjectivity of manual interpretation. DIP is a non-destructive, inexpensive and rapid method that has been used by many researchers in various applications of biofuel. In fuel science, DIP and artificial intelligence (AI) techniques have been successfully applied for the classification of biodiesel, selection of biomass for biofuel production. DIP can be used in the combustion process and its control parameters, gas leakage, monitoring fuel reactant conversion reactions, impurities present and adulteration of fuel, also automation process of a fuel injection system. This review gives an overview of the applications of image processing in fuel science. |
| Databáze: | OpenAIRE |
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