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MATHEMATICAL MORPHOLOGY I.INTRODUCTION II.BINARY MORPHOLOGY III.GREY-LEVEL MORPHOLOGY
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INTRODUCTION Mathematical morphology Self-sufficient framework for image processing and analysis, created at the École des Mines (Fontainebleau) in 70’s by Jean Serra, Georges Mathéron, from studies in science materials Conceptually simple operations combined to define others more and more complex and powerful Simple because operations often have geometrical meaning Powerful for image analysis
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INTRODUCTION Binary and grey-level images seen as sets X XcXc f (x,y) X = { (x, y, z), z f (x,y) }
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Operations defined as interaction of images with a special set, the structuring element INTRODUCTION
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MATHEMATICAL MORPHOLOGY I.INTRODUCTION II.BINARY MORPHOLOGY III.GREY-LEVEL MORPHOLOGY
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BINARY MORPHOLOGY 1.Erosion and dilation 2.Common structuring elements 3.Opening, closing 4.Properties 5.Hit-or-miss 6.Thinning, thickenning 7.Other useful transforms : i.Contour ii.Convex-hull iii.Skeleton iv.Geodesic influence zones
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X B BINARY MORPHOLOGY No necessarily compact nor filled A special set : the structuring element -2 -1 0 1 2 Origin at center in this case, but not necessarily centered nor symmetric Notation x y
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Dilation : x = (x 1,x 2 ) such that if we center B on them, then the so translated B intersects X. X B difference BINARY MORPHOLOGY
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Dilation : x = (x 1,x 2 ) such that if we center B on them, then the so translated B intersects X. How to formulate this definition ? 1) Literal translation 2) Better : from Minkowski’s sum of sets
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BINARY MORPHOLOGY Minkowski’s sum of sets : l l
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BINARY MORPHOLOGY Dilation : l Dilation
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l BINARY MORPHOLOGY Dilation is not the Minkowski’s sum
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l l bbbb l BINARY MORPHOLOGY
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Dilation with other structuring elements BINARY MORPHOLOGY
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Dilation with other structuring elements
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Erosion : x = (x 1,x 2 ) such that if we center B on them, then the so translated B is contained in X. BINARY MORPHOLOGY difference
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BINARY MORPHOLOGY 2) Better : from Minkowski’s substraction of sets Erosion : x = (x 1,x 2 ) such that if we center B on them, then the so translated B is contained in X. How to formulate this definition ? 1) Literal translation
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BINARY MORPHOLOGY
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Erosion with other structuring elements BINARY MORPHOLOGY
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Did not belong to X BINARY MORPHOLOGY Erosion with other structuring elements
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BINARY MORPHOLOGY Common structuring elements shapes = origin x y Note : circledisk segments 1 pixel wide points
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BINARY MORPHOLOGY Problem :
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BINARY MORPHOLOGY
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Problem : BINARY MORPHOLOGY d/2 d <d/2
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BINARY MORPHOLOGY Implementation : very low computational cost 0 1 (or >0) Logical or
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0 1 BINARY MORPHOLOGY Implementation : very low computational cost Logical and
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Opening : BINARY MORPHOLOGY Supresses : small islands ithsmus (narrow unions) narrow caps difference also
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Opening with other structuring elements BINARY MORPHOLOGY
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Closing : BINARY MORPHOLOGY Supresses : small lakes (holes) channels (narrow separations) narrow bays also
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BINARY MORPHOLOGY Closing with other structuring elements
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BINARY MORPHOLOGY Application : shape smoothing and noise filtering
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BINARY MORPHOLOGY Application : segmentation of microstructures (Matlab Help) original negated threshold disk radius 6 closing opening and with threshold
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BINARY MORPHOLOGY Properties all of them are increasing : opening and closing are idempotent :
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dilation and closing are extensive erosion and opening are anti-extensive : BINARY MORPHOLOGY
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duality of erosion-dilation, opening-closing,...
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structuring elements decomposition BINARY MORPHOLOGY operations with big structuring elements can be done by a succession of operations with small s.e’s
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Hit-or-miss : BINARY MORPHOLOGY “Hit” part (white) “Miss” part (black) Bi-phase structuring element
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Looks for pixel configurations : BINARY MORPHOLOGY doesn’t matter background foreground
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BINARY MORPHOLOGY isolated points at 4 connectivity
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Thinning : BINARY MORPHOLOGY Thickenning : Depending on the structuring elements (actually, series of them), very different results can be achieved : Prunning Skeletons Zone of influence Convex hull...
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Prunning at 4 connectivity : remove end points by a sequence of thinnings BINARY MORPHOLOGY 1 iteration =
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BINARY MORPHOLOGY 1st iteration 2nd iteration3rd iteration: idempotence
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BINARY MORPHOLOGY doesn’t matter background foreground What does the following sequence ?
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BINARY MORPHOLOGY 1.Erosion and dilation 2.Common structuring elements 3.Opening, closing 4.Properties 5.Hit-or-miss 6.Thinning, thickenning 7.Other useful transforms : i.Contour ii.Convex-hull iii.Skeleton iv.Geodesic influence zones
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i. Contours of binary regions : BINARY MORPHOLOGY
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4-connectivity 8-connectivity contour 8-connectivity 4-connectivity contour Important for perimeter computation.
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ii. Convex hull : union of thickenings, each up to idempotence BINARY MORPHOLOGY
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iii. Skeleton : BINARY MORPHOLOGY Maximal disk : disk centered at x, D x, such that D x X and no other D y contains it. Skeleton : union of centers of maximal disks.
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BINARY MORPHOLOGY Problems : Instability : infinitessimal variations in the border of X cause large deviations of the skeleton not necessarily connex even though X connex good approximations provided by thinning with special series of structuring elements
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BINARY MORPHOLOGY 1st iteration
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BINARY MORPHOLOGY result of 1st iteration 2nd iteration reaches idempotence
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BINARY MORPHOLOGY 20 iterations thinning 40 iterations thickening
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BINARY MORPHOLOGY Application : skeletonization for OCR by graph matching
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BINARY MORPHOLOGY and 3 rotations Hit-or-Miss
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iv. Geodesic zones of influence : BINARY MORPHOLOGY X set of n connex components {X i }, i=1..n. The zone of influence of X i, Z(X i ), is the set of points closer to some point of X i than to a point of any other component. Also, Voronoi partition. Dual to skeleton.
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BINARY MORPHOLOGY threrosion 7x7 GZIopening 5x5 and
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BINARY MORPHOLOGY
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threrosion 7x7 dist
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