在分析Gabor滤波器进行图像纹理特征提取的基础上,提出了利用多尺度和多方向Gabor滤波系数的高阶矩提取图像特征进行CBIR的方法,利用滤波系数的方差给出了基于Gabor滤波组提取的图像纹理特征的平滑度和纹理一致性算法,并采用四个尺度和六个方向的滤波系数的能量、方差、峰态、平滑度和一致性组成了CBIR特征向量。采用Brodatz纹理库和Corel图像库中的典型图像进行了对比实验。实验证明,提出的方法比传统的Gabor滤波进行CBIR具有更高的查准率。
A new Content-Based Image Retrieval (CBIR) method based on the high-order moments of multi-scale and multi-direction Gabor filtering coefficients was presented and the algorithm for measuring the features of smoothness and consistency of texture which was extracted by a Gabor filter bank was given by using the variance of filtering coefficients. The feature vector for CBIR is composed of the values of the energy, variance, kurtosis, smoothness and consistency of filtering coefficients in 4 scales and 6 directions. The typical images from Brodatz texture database and Corel images were utilized in the contrast experiments, which show that the proposed method gives better precision than traditional Gabor filtering method.