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多级小波分解与LBP融合的纹理提取算法
引用本文:韩拓荒,康志伟.多级小波分解与LBP融合的纹理提取算法[J].微计算机信息,2012(3):135-136,170.
作者姓名:韩拓荒  康志伟
作者单位:湖南大学信息科学与工程学院
摘    要:为提高不同光照、不同角度条件下的纹理识别精度,提出了一种利用多级小波分解和多尺度旋转不变LBP融合的纹理提取算法。算法在传统的LBP特征提取基础上,采用多尺度的旋转不变LBP算子分别对多级小波逼近图像提取直方图序列特征向量,与各级小波能量进行加权融合,获取更多的纹理信息,对光照和角度的变化有更高的鲁棒性。仿真结果表明,相对传统的LBP特征提取算法,改进的算法具有更高的纹理识别率。

关 键 词:纹理识别  LBP算子  直方图序列特征向量  小波能量

A Texture Extraction Method by Fusion of Multi-level Wavelet Decomposition and LBP
HAN Tuo-huang,KANG Zhi-wei.A Texture Extraction Method by Fusion of Multi-level Wavelet Decomposition and LBP[J].Control & Automation,2012(3):135-136,170.
Authors:HAN Tuo-huang  KANG Zhi-wei
Affiliation:(College of Information Science and Engineering,Hunan University,ChangSha,410082,China)
Abstract:To improve the texture recognition accuracy under the condition of different illumination and angles,a texture extraction method by fusion of multi-level wavelet decomposition and LBP operator is proposed based on the traditional LBP feature extraction.The rotation invariant LBP algorithm which is multi-resolution was used to extract the Histogram sequence feature vector from the multi-level wavelet approximation image and each levels of wavelet energy weighted fusion for more information on the texture.Under the different illumination and angles it is higher robustness.The emulation show that improved texture algorithm have higher recognition rate compared with traditional algorithm.
Keywords:texture recognition  LBP operator  histogram sequence feature vector  wavelet energy
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