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Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

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Page 1: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Local Symmetry - 2D

Ribbons, SATs and Smoothed Local Symmetries

Asaf YaffeImage Processing Seminar, Haifa University, March 2005

Page 2: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Outline Symmetry and Shape Description

Ribbons

Symmetry Axis Transform (SAT)

Smoothed Local Symmetries (SLS)

Page 3: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Symmetry and Shape Description

Page 4: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Global Symmetry Every symmetry element concerns the

whole image or shape All points in the object contribute to

determining the symmetry Behind the scope of this presentation…

Page 5: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Local Symmetry Symmetry elements are local to a subset

of the image or shape The subset is a continuous section of the

shape’s contour Generally used for shape description

Compact codingShape recognition

Page 6: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Motivation for Local Symmetry In many vision systems (e.g., robotics),

shape is represented in terms of global features:Centers of area/mass, number of holes,

aspect ration of the principal axes Global features can be computed

efficiently But…

Page 7: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Motivation for Local Symmetry Global features cannot be used to

describe occluded objectsA feature’s value of the visible portion has no

relationship to the value of the whole object Therefore, it is nearly impossible to

recognize occluded parts using global features

Hence, the need for local features

Page 8: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Shape Description Contour-based Representations

Chain-code, Fourier descriptors… Region-based Representations

Axial representations (MAT)… Shape descriptor properties

Generative: reconstruct the shape from its descriptor

Recoverable: create a unique descriptor for a shape

Page 9: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

General Terms and Definitions Normal - אנך Tangent - משיק Curvature - עקמומיות Perpendicular – ניצב/מאונך Oblique - אלכסוני Concave - קעור Convex – קמור Contour – מתאר Planar – מישורי

Page 10: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Ribbons

Page 11: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

What is a Ribbon? A planar shape Locally symmetric around an arc called

“axis” or “spine”

Page 12: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

What is a Ribbon?

S – Spine. Assume S is a simple, continuous arc with a tangent at every point

G – Generator. A simply connected set. May be of any shape

O – Center. Generator’s reference point (center) GO – Generator centered at O.

S

O

GO

Page 13: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

What is a Ribbon?

G’s are geometrically similar and may differ only in size rO – Radius. The size of GO.

R – Ribbon. The union of all GO for all O S

SR

rO

GO

Page 14: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

What is a Ribbon?

Let O’ and O’’ be the endpoints for S bR – the border of R. The border is smooth

Ribbon ends – parts of the border that are in GO’ or GO’’ but not in any other GO

Ribbon sides – the remaining parts of the border of R.

Page 15: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Requirements GO moves along S S is a simple arc G’s should not intersect (well… sort of… hard to

define…)

G’s must be maximal. Otherwise R may not follow the shape of its spine.

Page 16: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Requirements In all cases which follow, G is symmetric

about its center O. The symmetry of G tends to make R

“locally symmetric”. This, however, does not imply global

symmetry

Page 17: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Ribbon Classes “Blum” Ribbons (Blum, 1967, 1978)

“L-Ribbons”

“Brooks” Ribbons (Brooks, 1981)

“Brady” Ribbons (Brady, 1984)

Page 18: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Blum Ribbons Ribbons generated by disks centered on

the spine

The disks are circles with varying radii

Page 19: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Blum Ribbons are Recoverable Theorem: “If R is a Blum ribbon, the spine

and generators of R are uniquely determined”

Proof:Proposition 1: “If R is simply connected and its

border bR smooth, then any maximal disk D contained in R is tangent to bR”

Page 20: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Proof (cont.)Proposition 2: “If R is a Blum ribbon, every

maximal disk D contained in R is one of the G’s (and has its center on S)”

Corollary: “The set of maximal disks is the same as the set of G’s”

Let A = {DP | P bR} be the set of all maximal disks tangent to the border of R

By proposition 1, A contains all maximal disksBy proposition 2, A is identical to the set of all

G’s. The spine S is the locus of their centers

Page 21: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Blum Ribbons Limitations A Thick Blum ribbon cannot have points of high

positive curvature on its border

A Thick Blum ribbon cannot turn rapidly

The “non-self-intersection” requirement is hard to define

Page 22: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

L-Ribbons Ribbons generated by a line segment with

its midpoint on the spine The length and orientation of the line may

vary as it moves along the spine

The sides of R are the loci of the lines’ endpoints The ends of R are the lines at the ends of the spine

Page 23: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

L-Ribbon Properties The “non-self-intersection” requirement is

easily definedGenerators may not intersect

More flexible than Blum ribbonsThick ribbons can make sharp turnsCan have points of high positive (or negative)

curvature on their borders

Page 24: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

L-Ribbon Properties

L-Ribbons may have long protuberances on their borders as long as every point is visible from the spine

Page 25: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Highly ambiguous Same shape can be generated in many different ways

Need to apply constraints on the definition…

L-Ribbons Difficulties

Page 26: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Brooks Ribbons The generator is required to make a fixed

angle with the spineWe assume that the angle is 90 degrees

This limits the ability of Brooks ribbons to make sharp turnsThe thickness cannot exceed twice the radius

of the curvature of the spineS

Page 27: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Brooks Ribbons If the sides of the ribbon are straight and

parallel, its spine and generators are uniquely determined

If the sides are not parallel, the spine need not be a straight line, and thus may not be unique

Page 28: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Brady Ribbons The generator always makes equal angles

with the sides of the ribbon

Page 29: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Brady Ribbons If the ribbon has just one straight side, its

spine and generators are uniquely determinedTheorem: if both sides are straight, the spine

is a segment of the angle bisector and the generators are perpendicular to the spine

In the general case, the spine and generators are not unique

Page 30: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Theorem proof:

- 1 = 2 - => = (2 - 1 ) / 2 is constant. Hence, all G’s are parallel

Brady Ribbons

1

2

Page 31: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Brady Ribbons Thick Brady ribbons can make sharp turns

Thus, there are Brady ribbons which are not Brooks ribbons

Every Blum ribbon is a Brady ribbon (ignoring the ends)

G

O

Page 32: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Special Cases If the spine is straight, and we ignore the

ends thenEvery Blum ribbon is a Brooks ribbon

Every Brooks ribbon is a Brady ribbon

Blum Brooks Brady

Page 33: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Special Cases Even if the spine is straight…

There are Brady ribbons which are not Brooks

There are Brooks ribbons which are not Blum

Blum Brooks Brady

Page 34: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Symmetry Axis Transform (SAT)

Page 35: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Symmetry Axis Transform The loci of the centers of all maximal disks

entirely contained within the shape The disks must touch the border of the

shape (at least in one section) Also known as Medial Axis Transform

(MAT)

Page 36: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Symmetry Axis Transform Captures the major axis of the shape and

its orientation Reflects local boundary formations (e.g,

corners) of the shape

Page 37: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

SAT “Skeleton” Points The centers of maximal disks can be classified

into 3 classes: End points: disks touching the border in one section Normal points: disks touching the border in 2 sections Branch points: disks touching the border in 3 or more

sections Major cause for problems, such as losing the symmetry axes

of rectangular shapes

Page 38: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

SAT Properties Piecewise smooth

Comprised of one or more smooth spines Recoverable

The SAT of a shape is uniquely determined Generative

A shape can be perfectly reconstructed from its SAT

Page 39: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

SAT Weaknesses Very sensitive to noise

May lose the symmetry axes of the shape

Page 40: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Smooth Local Symmetries (SLS)

Page 41: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Smooth Local Symmetries Defined in two parts

Determination of the local symmetryFormation of maximal smooth loci of these

symmetries

Page 42: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Determining Local Symmetry Let A, B be points on the shape’s border Let nA be the outward normal at A

Let nB be the inward normal at B A and B are locally symmetric if both angles of the

segment AB and the normals are the same

Page 43: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Determining Local Symmetry A point may have a local symmetry with

several points

Point A has local symmetry with both B and C

Page 44: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Forming the “Skeleton” The shape’s “skeleton” is the union of

symmetry axesAn axis is the formation of maximal smooth

loci of local symmetriesThe symmetry locus is the midpoint of the

segment connecting the local symmetry points

Page 45: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Smooth Local Symmetry Axes An axis describes some piece of the

contour and the regionThis portion is called a Cover

Some covers are wholly contained in other covers (subsumed)

Subsumed covers are of less importance but still convey useful information

Page 46: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Smooth Local Symmetry Axes

The short diagonal axes are subsumed

The diagonal axes are not subsumed

Page 47: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

SLS Difficulties May generate redundant spines

Difficult to compute An O(n2) algorithm exists which tests all pairs of

border points for local symmetry A faster algorithm exists which calculates an

approximation of the SLS

Page 48: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Comparing SLS and SAT

SLS SAT

Page 49: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

Summary Local symmetry can be used to describe

parts of shapes Local symmetry can be described in

various waysRibbonsSATSLS

Page 50: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005

References A. Rosenfeld. “Axial Representation of Shape”.

Computer Vision, Graphics and Image Processing, Vol. 33, pp. 156-173. 1986

M.J. Brady, and H. Asada. “Smooth Local Symmetries and Their Implementations”. Int. J. of Robotics Reg. 3(3). 1984

J.Ponce, "On Characterizing Ribbons and Finding Skewed Symmetries," Computer Vision, Graphics, and Image Processing, vol. 52, pp. 328-

340, 1990 H. Zabrodsky, “Computational Aspects of Pattern Characterization –

Continuous Symmetry”.pp. 13 – 21. 1993

Page 51: Local Symmetry - 2D Ribbons, SATs and Smoothed Local Symmetries Asaf Yaffe Image Processing Seminar, Haifa University, March 2005