高级检索
孙君顶, 毋小省. 纹理谱描述符及其在图像检索中的应用[J]. 计算机辅助设计与图形学学报, 2010, 22(3): 516-520.
引用本文: 孙君顶, 毋小省. 纹理谱描述符及其在图像检索中的应用[J]. 计算机辅助设计与图形学学报, 2010, 22(3): 516-520.
Sun Junding, Wu Xiaosheng. Content-Based Image Retrieval Based on Texture Spectrum Descriptors[J]. Journal of Computer-Aided Design & Computer Graphics, 2010, 22(3): 516-520.
Citation: Sun Junding, Wu Xiaosheng. Content-Based Image Retrieval Based on Texture Spectrum Descriptors[J]. Journal of Computer-Aided Design & Computer Graphics, 2010, 22(3): 516-520.

纹理谱描述符及其在图像检索中的应用

Content-Based Image Retrieval Based on Texture Spectrum Descriptors

  • 摘要: 为了提高纹理谱描述符的性能并降低其特征维数,在中心对称局部二值模式纹理谱描述符的基础上,提出一种融合局部区域中心像素以及灰度均值的改进纹理描述模式.首先根据图像局部区域内中心像素与其邻域像素间的灰度变化关系,定义了新的局部纹理模式;然后通过比较局部区域内灰度均值与图像全局灰度均值的大小,对局部纹理模式进行了增强处理.采用不同纹理图像库及不同的性能评价准则进行实验的结果表明,文中方法在基于内容图像检索中取得了较好的效果.

     

    Abstract: To improve the performance and decrease the dimension of the texture spectrum descriptors,a novel descriptor,named ICS-LBP,is proposed based on LBP(local binary pattern)and CS-LBP(center-symmetric local binary pattern).Compared to the gray-value difference between the center-symmetric pixels used in CS-LBP and the gray-value difference between the center pixel and its neighbors used in LBP,the new descriptor classifies local patterns with respect to the gray value difference of the central pixel and the center-symmetric pixels,and thus fully uses the texture information of the local area.In addition,the novel descriptor can be refined by comparing the average gray of local regions and the entire image.The descriptors have been tested on three texture databases with different evaluation criterions and the experimental results demonstrate plausible performance for texture image retrieval.

     

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