A multivariate Gaussian modeling for counting bananas

Authors

  • Senthilarasi M
  • Navarasy T M
  • Ram Kumar C
  • Mohamed Mansoor Roomi

DOI:

https://doi.org/10.14419/ijet.v7i2.22.11803

Published:

2018-04-20

Keywords:

Gaussian modeling, HSV color space, Maximum likelihood detection, Multivariational approach

Abstract

Agriculture industries play an important role in economic development. Many post harvest techniques are performed in these industries. Especially in fruit industries, grading is an important process. As per the grading standard, banana hands must have minimum of twelve banana fingers. In the current scenario, the banana fingers are counted manually which is laborious. In order to reduce manual work, this paper proposes an algorithm for performing an automatic counting system of banana fingers in a bunch/hand using image processing algorithms. The parameters of the Gaussian model is acquired from the samples of fruit distal ends. A multivariate Gaussian modeling is accomplished on HSV color model to detect the distal end of banana fingers using maximum likelihood detection.

 

References

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How to Cite

M, S., T M, N., Kumar C, R., & Mansoor Roomi, M. (2018). A multivariate Gaussian modeling for counting bananas. International Journal of Engineering & Technology, 7(2.22), 27–30. https://doi.org/10.14419/ijet.v7i2.22.11803
Received 2018-04-20
Accepted 2018-04-20
Published 2018-04-20