Study on Authentication of Classes of Tulsi Leaf for the Extraction of Medicinal Qualities Using Image Processing Technique

Authors

  • T. Vijayashree Department of Electronics and Control Engineering, Faculty of Electrical and Electronics Engineering, Sathyabama University, Chennai, Tamil Nadu, India.
  • A. Gopal CSIR, CEERI, Madras Complex, Taramani, Chennai, India.

DOI:

https://doi.org/10.9734/bpi/nper/v4/9338D

Keywords:

Tulsi leaf, morphological processing, Gray Level Co-occurrence Matrix (GLCM), zernike moments, entropy, Inverse Difference Moment (IDM)

Abstract

The leaf is extremely important in plant species. There are some leaves that have medicinal properties. Identification of leaf with look-alike is becoming a major task in day to day life. To overcome this, a computer vision technique that includes an image processing algorithm is used. The features and texture of the leaf are extracted using this technique, and the closest match is used to determine which class it belongs to. This paper discusses a morphological processing algorithm in which the signature parameter serves as the vein. Morphological processing includes the structuring element, that is a dilation and erosion process. Authenticating an image with its signature parameter will be the most efficient technique in terms of accuracy, outperforming other methods.

Published

2021-12-02

How to Cite

T. Vijayashree, & A. Gopal. (2021). Study on Authentication of Classes of Tulsi Leaf for the Extraction of Medicinal Qualities Using Image Processing Technique. Novel Perspectives of Engineering Research Vol. 4, 153–160. https://doi.org/10.9734/bpi/nper/v4/9338D