Estimation of fiber length and diameter distribution from SEM images

Image analysis often includes a. measurement process. It is \vell known that direct measurements on images may introduce biases that need to be corrected. In the case of image analysis of man-macle vitreous fibers, one needs to measure their diameter and their length, in order to obtai11 the diameter distribution, which one may want to weight by the le11gtl1 of the fibers, or by their volume. If one is genera.lly able to measure fiber diameters directly after some segmentation steps and correct any measurement bias by Miles-Lantuéjoul-like methods, one cannot access directly the fiber lengths in all cases, for example when both ends of the fibers are not always visible. In this paper \ve present three original methods, based 011 different assumptions, that allow to estimate both the unbiased diameter distribution and the mean le11gtl1 by diameter class i11 any configuration, which in turn allow to estiinate with a high degree of confidence any le11gtl1, surface or volume-weiglited diameter distribution. These methods were tested on simulated images, and yielded remarquable results.