Improved fiber diameter determination of nanofibers through image analysis using a hierarchical scaling approach

Abstract

The determination of nanofiber diameters from SEM images is the standard procedure in characterizing the fiber morphology of electrospun materials. Typically, fiber diameter determination is done manually – a time consuming step including subjective factors of the analyst. An automated approach should save time and reduce the subjective part of the operator. Recently several algorithms have been suggested which use image pre-processing such as picture segmentation or edge detection followed by fiber detection algorithms such as radon, Hough, thinning based centerline determination and Euclidian distance transformation including corrective steps such as intersection correction and post operations such as fitting. None of the procedures is perfect and they will all strongly depend on the fiber orientation and fiber density of the analyzed SEM image. On developing our own algorithms we found that the field of view with respect to the number of fibers is in particular crucial when fiber orientation based algorithms such as Hough and radon. By selecting the appropriate field of view, a robust algorithm was developed and the results were compared with manually analyzed SEM images and results from the recent open source tool DiameterJ