1. Grape Detection in Vineyards
Final project by
Yael Peretz & Amir Yeger

2. Introduction
Detecting grapes via color recognition and clustering.

3. Goals Circle recognition – unsuccessful Color filtering Clustering
Noise removal
Filling in non-desired filtered areas

4. Implementations Implementation #1: Color filtering Clustering
Result – better grape detection, poorer background filtering!

5. Implementations
Implementation #1 – Color filtering

6. Implementations
Implementation #1 – Clustering

7. Implementations
Implementation #1 – Result

8. Implementations Implementation #2: Color filtering
Result – better background filtering, poorer grape detection!

9. Implementations
Implementation #2 – Color Filtering

10. Implementations
Implementation #2 – Color Filtering

11. Implementations
Implementation #2 – Result

12. Results - 1

13. Results - 1
Implementation -1
Implementation -2

14. Results - 2

15. Results - 2
Implementation -1
Implementation -2

16. Result - 3

17. Result - 3
Implementation -1
Implementation -2

18. Results – 4

19. Result – 4
Implementation -1
Implementation -2

20. Conclusions Color filtering – not the perfect solution
Clustering – efficient, but with the use of good color filtering
Both algorithms achieved better results on images whose grapes had a lighter color than images with darker grapes

21. Questions?

22. No…? ok, thank you