Image Processing - Case Studies

Background:
Grain and pulse distribution relies on manual grading of shipments. The grading process is time-consuming and must be performed by a grading expert.
Key Features:
- Number of peas and lentils in the images
- Classification of the various kinds of lentils and peas
- List of classes (bleached, damaged, wrinkled, foreign, etc.)
- Technologies used - machine vision and machine learning
- Accuracy - 95%
Result
The application automatically identified the number of peas and the different qualities of the peas.