A thorough understanding and analysis of geometry and topology of three-dimensional fiber networks from high resolution images is an important and challenging task due to the enormous complexity and randomness of the structure. In this paper we propose a technique that is aimed at structural analysis of fiber mats, both for quality evaluation and improvement of fiber products. A sequence of image processing techniques is applied to the images, to obtain the medial axis of the fiber network. A description of the network is then determined from the medial axis. We demonstrate computational algorithms that can efficiently identify individual fibers from a network of randomly oriented and curled fibers that are bonded irregularly with each other. We can accurately measure the orientation, location, curl, length, bonds, and crossing angles of the identified fibers as well as the density of the fibers contained in a given volume. The performance of the proposed technique is presented for simulated fiber data and for a synthetic (polymer) fiber mat.
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