A Rotation-Invariant Approach to 2D Shape Representation Using the Hilbert Curve

@inproceedings{Armstrong2009ARA,
  title={A Rotation-Invariant Approach to 2D Shape Representation Using the Hilbert Curve},
  author={Jeffrey Armstrong and Maher Ahmed and Siu-Cheung Chau},
  booktitle={ICIAR},
  year={2009}
}
A novel approach to 2D shape representation which is invariant to the rotation is introduced. The proposed system determines how any given shape should be rotated depending on the principal axis of the image. After rotation, a space-filling curve is applied to obtain a 1D vector representation of the image. This vector is later compressed in order to obtain a very small 1D vector that adequately represents an image --- this is called the Shape Feature Vector (SFV). The system can import these… 
Alternative patterns of the multidimensional Hilbert curve
TLDR
Large-scale image retrieval tests show that exploring the image feature space with an alternative way to the classical Hilbert curve can lead to improved image searching performances.

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