获取木材显微图像中的细胞组织对于分析木材的种类、材性,以及天气变化等均有重要的意义,而这依赖于图像分割技术。针对木材组织的不均匀性,以及标本制作和获取过程中带来的噪声,将水平集方法中边缘型和区域型两种模型引入,同时结合局部图像信息来提高局部不均匀图像的分割性能。在图像初始分割基础上,通过面积阈值去除水泡等杂质,最终提取导管组织。实验结果表明,提出的模型所得到的分割图像较平滑,而且噪声明显减少,可有效分割局部不均匀木材显微图像。

Obtaining various tissues from microscopic of wood images has important significance for the analysis of wood properties, weather changes, and wood species, which relies on the results of image segmentation techniques. Level Set is conducted in the segmentation of wood images in our experiments described in this paper.After the combination of the edge-based and region-based models in Level Set,we introduce the local cues in image to improve the image segmentaion performance for the wood tissue's inhomogeneity and reduce the noise caused by the production of wood specimens. Then, an area threshold is used to get rid of blisters and other impurities in the image to obtain the wood pores at last. Experiments show that the proposed method can smoothly segment images of local non-uniform wood microstructure,and significantly reduced the noise.