Morphological Detection Method of Micron Wood Fiber Based on Skeleton Information

Abstract

In order to compensate for the lack of mathematical model support for the traditional study of fiber morphology, using polynomial fitting to build microns wood fiber morphological model based on skeleton information. The fiber morphological category can be distinguished by taking derivation of the fitting function. In order to overcome the disadvantages of common morphological detection, the measurement of fiber length and its degree of curvature by using skeleton information is carried out. The length of the skeleton is approximated as the true length of the wood fiber, and the projected length can be calculated according to the endpoint coordinates. Finally, the fiber's curl index was obtained. Through the experiment, it has verified rationality of the fiber morphology model, and it is proved that the measurement method based on skeleton information can be better to avoid the influence of wood fiber morphological changes to the length measuring accuracy, moreover the fiber curl index can be calculated to quantify the bending degree and the type of wood fiber. It is an effective morphological detection method.