access icon free Shape recognition using orientational and morphological scale-spaces of curvatures

© The Institution of Engineering and Technology
Received 08/01/2015, Accepted 19/02/2015, Published 24/04/2015

In this study, a scale-invariant representation for closed planar curves (silhouettes) is proposed. The orientations of all points within the Gaussian scale-space of the curve are extracted. This orientation scale-space is used to create the silhouette orientation image in which the positions of each pixel indicate the curve's pixel positions and scales, whereas the colour represents orientation. The representation is extracted for multiple levels of the morphological scale-space of the silhouette. The proposed representation is invariant to scale and transformable under planar rotation. Using linear and non-linear distance learning methods, experiments on the MPEG7, ETH80 and Kimia shape datasets were conducted, with results indicating an advanced recognition capability.

Inspec keywords: image colour analysis; shape recognition; Gaussian processes; mathematical morphology

Other keywords: ETH80; planar rotation; Gaussian scale-space; scale-invariant representation; linear distance learning method; closed planar curve; orientation scale-space; MPEG7; shape recognition; Kimia shape dataset; silhouette orientation image; nonlinear distance learning method; morphological scale-spaces

Subjects: Other topics in statistics; Image recognition; Other topics in statistics; Computer vision and image processing techniques

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