Computer Vision: Edge detect project

Results of an edge detection project are discussed.

Transcript

1. CIS 581: Computer Vision Ly, Pant
2. •Standard approach ◦ Local maxima ◦ Hysteresis •Different Thresholds for different images ◦ Threshold is a function of average gradient value and standard deviation of gradient value ◦ Threshold= mean + factor*std. deviation
3. •2 steps ◦ Find all local maximas. ◦ Keep only those maximas which are above the threshold. •Two matrices ◦ LM_H = (Mag_q > Mag_r or q = r) and (Mag_q > Mag_p or q = p) ◦ LM_L = LM_H | Mag_q > thresh_mag
4. •Mask_s = Mag_s > threshold_hys and LM_L •Mask_os = Mag_os > threshold_hys and LM_L •Hysteresis = LM_H and Mask_s and Mask_os
5. •Matrix-based approach •Computation of theta using cart2pol ◦ Questions regarding unit vector •Attempt at recursive hysteresis
6. Results
7. Results
8. Results
9. Results
10. Results
11. •Understand the algorithm •Ask more questions early •Start early (did this!) •Try the way you know first. Optimize later. •Edges too thick!
12. THANK YOU Questions?