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 language | English |
|---|---|
| Pages (from-to) | 229-238 |
| Number of pages | 10 |
| Journal | International Journal of Agricultural Extension |
| Volume | 9 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2021 |
| Externally published | Yes |
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