关键词: 纹理特征, Haar特征, LBP, 高斯加权矩阵

Abstract:

Due to strong subjectivity and poor locality of the artificial setting judgment threshold, in the process of extracting the Haar local binary texture (LBP), the extracted texture details and edges are not clear and the locality of texture image may be ignored. Therefore, we propose an adaptive Haar local binary pattern texture feature extraction algorithm, in which the Gaussian weighted matrix is introduced when the Haar characteristic is binarized. Subsequently the adaptive judgment threshold and the Haar local binary pattern which are objective and conform to the locality of texture image can be extracted. Experimental results show that the proposed algorithm can effectively avoid the influence of the artificial judgment threshold on texture feature and accurately describe the texture feature of images. Besides, the classification  accuracy for Brodatz texture datasets can also be further improved.

Key words: texture feature;Haar characteristic;local binary pattern;Gaussian weighted matrix