Slide 1

Slide 1 text

CIS 581: Computer Vision Ly, Pant

Slide 2

Slide 2 text

●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

Slide 3

Slide 3 text

●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

Slide 4

Slide 4 text

●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

Slide 5

Slide 5 text

●Matrix-based approach ●Computation of theta using cart2pol ○ Questions regarding unit vector ●Attempt at recursive hysteresis

Slide 6

Slide 6 text

Results

Slide 7

Slide 7 text

Results

Slide 8

Slide 8 text

Results

Slide 9

Slide 9 text

Results

Slide 10

Slide 10 text

Results

Slide 11

Slide 11 text

●Understand the algorithm ●Ask more questions early ●Start early (did this!) ●Try the way you know first. Optimize later. ●Edges too thick!

Slide 12

Slide 12 text

THANK YOU Questions?