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OBJECT RECOGNITION – BLOB ANALYSIS
Examples of form parameters that are invariant with respect to position, orientation, and scale: Number of holes in the object Compactness or Complexity: (Perimeter)2/Area Moment invariants All of these parameters can be evaluated during contour following.
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GENERALIZED MOMENTS Shape features or form parameters provide a high level description of objects or regions in an image Many shape features can be conveniently represented in terms of moments. The (p,q)th moment of a region R defined by the function f(x,y) is given by:
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GENERALIZED MOMENTS In the case of a digital image of size n by m pixels, this equation simplifies to: For binary images the function f(x,y) takes a value of 1 for pixels belonging to class “object” and “0” for class “background”.
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GENERALIZED MOMENTS X i j Mij 1 2 7 33 20 159 64 93 Y 1 2 3 4 5 6 7 8
1 2 1 2 3 4 5 6 7 8 9 7 Area 33 20 159 Moment of Inertia 64 93 Y
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SOME USEFUL MOMENTS The center of mass of a region can be defined in terms of generalized moments as follows:
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SOME USEFUL MOMENTS The principal axis of an object is the axis passing through the center of mass which yields the minimum moment of inertia. This axis forms an angle θ with respect to the X axis. The principal axis is useful in robotics for determining the orientation of randomly placed objects.
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Principal Axis: Derivation
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Example X Principal Axis Center of Mass Y
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SOME USEFUL MOMENTS The moments of inertia relative to the center of mass can be determined by applying the general form of the parallel axis theorem:
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SOME (MORE) USEFUL MOMENTS
The minimum/maximum moment of inertia about an axis passing through the center of mass are given by:
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SOME (MORE) USEFUL MOMENTS
The following moments are independent of position, orientation, and reflection. They can be used to identify the object in the image.
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SOME (MORE) USEFUL MOMENTS
The following moments are normalized with respect to area. They are independent of position, orientation, reflection, and scale.
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