●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
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●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
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●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
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●Matrix-based approach
●Computation of theta using cart2pol
○ Questions regarding unit vector
●Attempt at recursive hysteresis
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Results
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Results
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Results
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Results
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Results
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●Understand the algorithm
●Ask more questions early
●Start early (did this!)
●Try the way you know first. Optimize later.
●Edges too thick!