Incorporating Two First Order Moments into LBP-Based Operator for Texture Categorization
نویسندگان
چکیده
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.
منابع مشابه
A Framework for Analyzing Texture Descriptors
This paper presents a new unified framework for texture descriptors such as Local Binary Patterns (LBP) and Maximum Response 8 (MR8) that are based on histograms of local pixel neighborhood properties. This framework is enabled by a novel filter based approach to the LBP operator which shows that it can be seen as a special filter based texture operator. Using the proposed framework, the filter...
متن کاملMultivariate Texture-based Segmentation of Remotely Sensed Imagery for Extraction of Objects and Their Uncertainty
In this study, a segmentation procedure is proposed based on grey-level and multivariate texture to extract spatial objects from an image scene. Object uncertainty was quantified to identify transitions zones of objects with indeterminate boundaries. The Local Binary Pattern 2 (LBP) operator, modeling texture, was integrated into a hierarchical splitting segmentation to identify homogeneous tex...
متن کاملPLBP: An effective local binary patterns texture descriptor with pyramid representation
Local binary pattern (LBP) is an effective texture descriptor which has successful applications in texture classification and face recognition. Many extensions are made for conventional LBP descriptors. One of the extensions is dominant local binary patterns which aim at extracting the dominant local structures in texture images. The second extension is representing LBP descriptors in Gabor tra...
متن کاملA Novel Noise-Robust Texture Classification Method Using Joint Multiscale LBP
In this paper we describe a novel noise-robust texture classification method using joint multiscale local binary pattern. The first step in texture classification is to describe the texture by extracting different features. So far, several methods have been developed for this topic, one of the most popular ones is Local Binary Pattern (LBP) method and its variants such as Completed Local Binary...
متن کاملStatistical binary patterns for rotational invariant texture classification
A new texture representation framework called statistical binary patterns (SBP) is presented. It consists in applying rotation invariant local binary pattern operators (LBP) to a series of moment images, defined by local statistics uniformly computed using a given spatial support. It can be seen as a generalisation of the commonly used complementation approach (CLBP), since it extends the local...
متن کامل