基于Float-LBP算法的纹理图像检索

Texture images retrieval based on Float-LBP

局部二值模式(LBP)仅依赖中心点和其邻域点在灰度上的差异,忽略了邻域点之间的浮动关系,导致表征能力较差,因此提出了一种改进的LBP算法。在对图像LBP二值化前,首先将邻域点按顺时针方向和其相邻的点进行比较得到一串类似于LBP算子的二进制序列;然后对这一序列进行十进制编码,并将这一部分的特征记作FloatLBP(F-LBP);最后再和原始的LBP算子提取的特征结合作为整幅图像的纹理特征。实验表明,通过F-LBP和LBP算子的结合,在保留局部微观纹理的前提下增加了更多的图像纹理分布信息,提高了算法的检索精度。

An improved method based on Local Binary Pattern （LBP） was proposed to solve the problem that the representing ability of LBP is bad because only the relationship between neighbors and the central pixels are considered while the floating relationship of the gray values in the neighbor region is ignored. Firstly, each neighbor was compared clockwise with its next adjacent neighbor before threshold and an LBP-like code was generated. Secondly, the code was encoded to a decimal number named as Float-LBP （ F-LBP）. Thirdly, the features extracted by the F-LBP and the basic LBP operators were combined together. The experimental results show that the combination of the F-LBP and the basic LBP operators can improve the retrieval accuracy by extracting more discriminative information while reserving the local micro-texture.