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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

Incorporating Two First Order Moments into LBP-Based Operator for Texture Categorization

verfasst von : Thanh Phuong Nguyen, Antoine Manzanera

Erschienen in: Computer Vision - ACCV 2014 Workshops

Verlag: Springer International Publishing

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Abstract

Within different techniques for texture modelling and recognition, local binary patterns and its variants have received much interest in recent years thanks to their low computational cost and high discrimination power. We propose a new texture description approach, whose principle is to extend the LBP representation from the local gray level to the regional distribution level. The region is represented by pre-defined structuring element, while the distribution is approximated using the two first statistical moments. Experimental results on four large texture databases, including Outex, KTH-TIPS 2b, CUReT and UIUC show that our approach significantly improves the performance of texture representation and classification with respect to comparable methods.

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Vorheriges Kapitel Local Associated Features for Pedestrian Detection
Nächstes Kapitel Log-Gabor Weber Descriptor for Face Recognition
Fußnoten
1
Note that a moment image corresponds to a local filter defined by a statistical moment, and should not be confused with the concept of “image moment”.
 
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Metadaten
Titel
Incorporating Two First Order Moments into LBP-Based Operator for Texture Categorization
verfasst von
Thanh Phuong Nguyen
Antoine Manzanera
Copyright-Jahr
2015
Buch
Computer Vision - ACCV 2014 Workshops

Print ISBN: 978-3-319-16627-8

Electronic ISBN: 978-3-319-16628-5

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-16628-5_38

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