计算机技术与发展2016，Vol.26Issue(10)：11-16,6.DOI:10.3969/j.issn.1673-629X.2016.10.003
融合LBP纹理和局部灰度特征的材料图像分割
Material Image Segmentation Combined LBP Texture and Local Gray Level Feature
摘要
Abstract
To improve precision of material image segmentation,based on spectral clustering method,a set of new algorithms combined local gray level features with Local Binary Patterns ( LBP) are proposed. Considering that the LBP operator cannot efficiently distinguish the difference of gray magnitude of pixels in the neighborhoods,several threshold-LBP ( T-LBP) operators are proposed to show the change of image pixels. The difference of neighborhood vector is constructed to describe the local features,selecting sample points by gray level histogram,establishing the similarity matrix by combination of T-LBP features,gray features of pixel and local features,conducting the image segmentation by spectral clustering algorithm,and constraining the texture noise with direction by liner detection. The experi-ment for ceramic material image and synthetic image shows that the algorithm has high segmentation precision,strong noise resistance, and well correct classification rate. The proposed algorithm breaks through the drawbacks and improves the accuracy of material image segmentation,which is appropriate for various areas and complex texture of material images. The comparison among the proposed algo-rithm and other algorithm demonstrates the effectiveness of the former.关键词
图像分割/T-LBP/谱聚类算法/灰度特征/线检测Key words
image segmentation/T-LBP/spectral clustering algorithm/gray level/line detection分类
信息技术与安全科学引用本文复制引用
赵曌,丁广太,樊明磊,张惠然,王路,陈琳..融合LBP纹理和局部灰度特征的材料图像分割[J].计算机技术与发展,2016,26(10):11-16,6.基金项目
上海市政府科研计划项目(14DZ2261200) （14DZ2261200）
