Rotated Local Binary Pattern (RLBP) - Rotation Invariant Texture Descriptor
نویسندگان
چکیده
In this paper we propose two novel rotation invariant local texture descriptors. They are based on Local Binary Pattern (LBP), which is one of the most effective and frequently used texture descriptor. Although LBP efficiently captures the local structure, it is not rotation invariant. In the proposed methods, a dominant direction is evaluated in a circular neighbourhood and the descriptor is computed with respect to it. The weights associated with the neighbouring pixels are circularly shifted with respect to this dominant direction. Further, in the second descriptor, the uniformity of the patterns is utilized to extract more discriminative information. The proposed methods are tested for the task of texture classification and the performance is compared with original LBP and its existed extensions.
منابع مشابه
Dominant Rotated Local Binary Patterns (DRLBP) for texture classification
In this paper, we present a novel rotation-invariant and computationally efficient texture descriptor called Dominant Rotated Local Binary Pattern (DRLBP). A rotation invariance is achieved by computing the descriptor with respect to a reference in a local neighborhood. A reference is fast to compute maintaining the computational simplicity of the Local Binary Patterns (LBP). The proposed appro...
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 کاملRLBP: Robust Local Binary Pattern
In this paper, we propose a simple and robust local descriptor, called the robust local binary pattern (RLBP). The local binary pattern (LBP) works very successfully in many domains, such as texture classification, human detection and face recognition. However, an issue of LBP is that it is not so robust to the noise present in the image. We improve the robustness of LBP by changing the coding ...
متن کاملRotationally Invariant Hashing of Median Binary Patterns for Texture Classification
We present a novel image feature descriptor for rotationally invariant 2D texture classification. This extends our previous work on noise-resistant and intensity-shift invariant median binary patterns (MBPs), which use binary pattern vectors based on adaptive median thresholding. In this paper the MBPs are hashed to a binary chain or equivalence class using a circular bit-shift operator. One bi...
متن کاملShearing invariant texture descriptor from a local binary pattern and its application in paper fingerprinting
In this paper, a Shearing Invariant Texture Descriptor (SITD) is proposed, which is a theoretically and computationally simple method based on the Rotation invariant Local Binary Pattern (Rot-LBP) descriptor. In real-world applications using flatbed scanners, such as paper texture fingerprinting, it’s common for a sheet of paper to rotate during the image acquisition process. Because the rotati...
متن کامل