Hi, I've been playing around with the binary_hit_or_miss function in the nd_image and it seems to work well in general. I understand that binary thinning can be generated by using hit_or_miss, however I can't seem to get it to work right. Anyone have a code snippet that does the job? I follow the procedure at: http://homepages.inf.ed.ac.uk/rbf/HIPR2/thin.htm My implementation is as follows: ## from HIPR2 web site ## [0,0,0] ## [x,1,x] ## [1,1,1] struct1 = numarray.array( [[0, 0, 0], [0, 1, 0], [1, 1, 1]]) struct2 = numarray.array( [[1, 1, 1], [0, 0, 0], [0, 0, 0]]) ## [x,0,0] ## [1,1,0] ## [x,1,x] struct3 = numarray.array( [[0, 0, 0], [1, 1, 0], [0, 1, 0]]) struct4 = numarray.array( [[0, 1, 1], [0, 0, 1], [0, 0, 0]]) b = [] for i in range(4): temp = ND.binary_hit_or_miss(a, struct1, struct2) b.append(temp) temp = ND.binary_hit_or_miss(a, struct3, struct4) b.append(temp) struct1 = ND.rotate(struct1, 90) struct2 = ND.rotate(struct2, 90) struct3 = ND.rotate(struct3, 90) struct4 = ND.rotate(struct4, 90) result = b[0] for i in range(7): result = numarray.logical_or(result, b[i+1]) result = a - result Bob
participants (2)
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Bob Klimek
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Peter Verveer