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Computation of the Local Binary Pattern (LBP) descriptor of large scale images

Authors: Chen, Joshua;

Computation of the Local Binary Pattern (LBP) descriptor of large scale images

Abstract

Local binary patterns (LBPs) are powerful texture descriptors that have recently found several applications in medical image analysis. Research in this field is currently directed towards parallel implementations suitable for processing large scale images. Programming tool-sets such as the Open Computing Language (OpenCL) opened up opportunities for the development of various parallel algorithms and applications for General-Purpose GPU (GPGPU), all executable across heterogeneous OpenCL compliant platforms. In this report, we give an introduction to the LBP texture descriptor and the OpenCL framework. We will also discuss the computation of LBP descriptors for high resolution tissue images of biopsy samples, and outline various implementation aspects of the algorithm in OpenCL. Experiments were conducted on consumer-grade graphical processing units (GPUs) and a central processing unit (CPU), addressing relations to more than algorithmic complexities but limits on physical resources too.

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New Zealand
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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