Shape and texture based classification of citrus using principal component analysis

Naeem Akhter, Muhammad Idrees, Furqan Ur Rehman, Muhammad Ilyas*, Qaiser Abbas, Muhammad Luqman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Citrus family consists of a variety of eatable, consumable and usable items with varying nutritional contents. Naked eye citrus classification needs expert human effort, which provides poor decision reliability. The unreliable classification decision may be extremely hazardous when the citrus is being classified for exports or usage in pharmacy products and various food items. In this paper, citrus fruit has been classified on shape and texture features. Principal Component Analysis (PCA) was used as a methodology to explore statistical findings. The average accuracy of the system proposed is 84%. This system can be implemented on pharmacy stores, food production units, or industries, and citrus export centers for reliable citrus fruit classification.

Original languageEnglish
Pages (from-to)229-238
Number of pages10
JournalInternational Journal of Agricultural Extension
Volume9
Issue number2
DOIs
StatePublished - 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2020.

Keywords

  • Angular second moment
  • Bitmap image (BMP)
  • Contrast
  • Correlation
  • Image processing (IP)
  • Region of interest (ROI)

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Plant Science

Fingerprint

Dive into the research topics of 'Shape and texture based classification of citrus using principal component analysis'. Together they form a unique fingerprint.

Cite this