Rotation invariant texture classification using LBP variance (LBPV) with global matching
نویسندگان
چکیده
Local or global rotation invariant feature extraction has been widely used in texture classification. Local invariant features, e.g. local binary pattern (LBP), have the drawback of losing global spatial information, while global features preserve little local texture information. This paper proposes an alternative hybrid scheme, globally rotation invariant matching with locally variant LBP texture features. Using LBP distribution, we first estimate the principal orientations of the texture image and then use them to align LBP histograms. The aligned histograms are then in turn used to measure the dissimilarity between images. A new texture descriptor, LBP variance (LBPV), is proposed to characterize the local contrast information into the one-dimensional LBP histogram. LBPV does not need any quantization and it is totally training-free. To further speed up the proposed matching scheme, we propose a method to reduce feature dimensions using distance measurement. The experimental results on representative databases show that the proposed LBPV operator and global matching scheme can achieve significant improvement, sometimes more than 10% in terms of classification accuracy, over traditional locally rotation invariant LBP method. & 2009 Elsevier Ltd. All rights reserved.
منابع مشابه
Performance Analysis of Local Binary Pattern Variants in Texture Classification
-Texture classification is a major issue in image analysis and pattern recognition. A number of methods are proposed in the literature including Local Binary Pattern (LBP). The LBP variant (s) plays an active role to extract texture features for texture classification. These are rotation invariant, noise sensitive or noise insensitive mehods. Each method has its own advantages and disadvantages...
متن کاملA Rotation-invariant Script Identification based on BEMD and LBP
Script identification is very important to develop the scripts OCR systems. In this paper, we proposed a new algorithm for script identification based on the global and local texture of document images. The BEMD method is used to decompose the image to some components (IMFs) and then the Local Binary Patterns (LBP) method is used to detect the features. Experiments shown the recognition rate ba...
متن کاملTexture classification using rotation invariant models on integrated local binary pattern and Zernike moments
More and more attention has been paid to the invariant texture analysis, because the training and testing samples generally have not identical or similar orientations, or are not acquired from the same viewpoint in many practical applications, which often has negative influences on texture analysis. Local binary pattern (LBP) has been widely applied to texture classification due to its simplici...
متن کاملCompleted Local Ternary Pattern for Rotation Invariant Texture Classification
Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that redu...
متن کاملRotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features
In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Pattern Recognition
دوره 43 شماره
صفحات -
تاریخ انتشار 2010