What is the main reason for rotational invariance of LBPP, R texture descriptor compared to LBPp

step 1 As you can see, this is a 90 -degree rotation. It's a quarter turn because if there's 360 degree

What is the main reason for rotational invariance of LBPP, R...

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Key Concepts

Rotational Invariance

Rotational invariance refers to the property of a descriptor to remain consistent even if the image or texture is rotated. In texture analysis, this is crucial because a texture's appearance should be recognized regardless of its orientation. Achieving rotational invariance means that the descriptor captures the intrinsic properties of the texture rather than its spatial arrangement in a fixed direction.

Local Binary Patterns (LBP)

The Local Binary Pattern operator is a texture descriptor that summarizes the local structure around each pixel by comparing neighboring pixel intensities to the center pixel. This method converts the local differences into a binary code, effectively capturing the texture’s micro-structures. However, the standard LBP is sensitive to rotation unless modified for invariance.

Cyclic Shift Normalization

A key modification to achieve rotational invariance in descriptors like LBPP,R is the application of a cyclic shift normalization. By rotating (or cyclically shifting) the binary pattern to a canonical form—typically by selecting the minimum value among all rotated versions—the descriptor becomes invariant to the starting point of the circular sampling. This mechanism underpins the rotational invariance of LBPP,R compared to the conventional LBP operator.

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