基于改进归一化距离匹配函数的纹理周期自动提取方法

摘要

Based on improved normalized distance matching function ( INDMF ) , an automatic extraction method for regular and near_regular structural texture periodicity is proposed. Firstly, the dissimilarity of gray level co_occurrence matrices is calculated as the texture characteristic, and the INDMF edge is removed. Thus, the values between different peak intervals are more stable. Secondly, an adaptive and anti_noise peak searching approach is adopted to find initial periodic sequence and extract texture periodicity. Next, with the consideration of the characteristics of artificial and natural texture, the final periodicity is calculated by sequence mode. The results of extraction experiments on Brodatz and PSU datasets show the effectiveness and the efficiency of the proposed method. Moreover, the proposed method is more stable and accurate than the method of forward difference of accumulative DMF for impulsive salt and pepper noisy images and projective deformed images.%针对规则纹理和近似规则纹理，提出基于改进归一化距离匹配函数( INDMF)的纹理周期自动提取方法。该方法首先利用灰度共生矩阵的差异性作为纹理特征，去除改进归一化匹配函数的边缘，有效优化函数峰值间的稳定性。然后使用自适应峰值寻找算法去除噪声干扰，获得初始峰值序列并进行周期提取。最后使用众数计算最优周期。分别对Brodatz纹理和PSU周期纹理进行提取实验，结果显示文中方法运行效率较高，能有效提取自然纹理的结构周期。与累加DMF向前差分法相比，文中方法具有更好的抗噪声和抗畸变能力。