Vectorised SIMD Implementations of Morphology Algorithms

Cree, Michael J.

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Cree, M. J. (2015). Vectorised SIMD Implementations of Morphology Algorithms. In Proceedings of the Image and Vision Computing New Zealand, 23-24 November 2015, Auckland, New Zealand.

Permanent Research Commons link: https://hdl.handle.net/10289/9785

Abstract

We explore vectorised implementations, exploiting single instruction multiple data (SIMD) CPU instructions on commonly used architectures, of three efficient algorithms for morphological dilation and erosion. We discuss issues specific to SIMD implementation and describe how they guide algorithm choice. We compare our implementations to a commonly used opensource SIMD accelerated machine vision library and find orders of magnitude speed-ups can be achieved for erosions using two-dimensional structuring elements.

Date

2015

Type

Conference Contribution

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This is an author’s accepted version of an paper published in the proceedings of Image and Vision Computing New Zealand 2015. ©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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