India is notable for its traditional medicinal leaves. These leaves are not just utilised in home cures which involve use of leaves in regular household ingredients, they are utilised as an emergency treatment for a few common ailments like cough, fever, cold, etc. in Ayurveda. These medicinal leaves hold a superior healing power which varies significantly according to their maturity. The practices that were taken to detect the maturity level of leaves using chemical analysis were much more expensive and tedious. To develop a system to classify the medicinal leaves with their maturity, we have used hyperspectral imaging. We have used three medicinal leaf species which are Tulsi, Neem, and Pudina. For capturing hyperspectral images, we have used a specialised hyperspectral camera. These images give more information about leaves. After collecting the required information for each leaf, some ML classifier models like Support Vector Machine (SVM), Random Forest Classifier, and Logistic Regression were implemented with accuracy scores obtained was 99.76%, 66.91%, and 87.77% respectively. Each species has a subclass of Dry and Fresh which will be verified and tested properly with multiple runs along with its maturity level.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Medicinal Leaves Classification Using Hyperspectral Imaging


    Additional title:

    Smart Innovation, Systems and Technologies



    Conference:

    Congress on Control, Robotics, and Mechatronics ; 2024 ; Warangal, India February 03, 2024 - February 04, 2024



    Publication date :

    2024-11-14


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    ROBUST FOREST CLASSIFICATION USING HYPERSPECTRAL IMAGING, LASFR SCANNING AND SATELLITE IMAGERY

    Mosin, Vasilii / Platonov, Alexander / Aguilar, Roberto et al. | TIBKAT | 2020


    Hyperspectral Imaging

    Gravel, D. | British Library Conference Proceedings | 1997


    Polarimetric Hyperspectral Imaging

    Cheng, L. / Reyes, G. | NTRS | 1994


    Polarimetric Hyperspectral Imaging

    Cheng, L-J. | NTRS | 1994


    Hyperspectral Texture Classification Using Generalized Markov Fields

    Sarkar, S. / Healey, G. / IEEE Computer Society | British Library Conference Proceedings | 2004