No, I have not tried these more complex approaches favored by biologists as they deal with curved objects and they seldom focus on the determination of the exact fiber length distribution values; we don't care about the width (we know its value a priori), but we worry about fibers crossing, touching, sticking together.
Frankly, my interest in image recognition and processing is very utilitarian and results-oriented, a procedure I can develop and pass on to our technicians to use reliably. It is also limited to a specific materials system which always contains chopped or milled rigid and brittle fibers. Snake-like, oval, round, irregular and floppy objects are of no interest to me, and this is also probably true of anybody working on the analysis of fiber-reinforced polymer composites (https://goo.gl/lq6te6).
I also feel that any object recognition, segmentation and classification program or plugin that cannot resolve these seven lines correctly is failing a qualifying test; it seems to me that a proposed algorithm should first demonstrate that it is capable of correctly detecting the lines, then other, progressively more difficult shapes, such as ovals, circles, squares, rectangles--and only then moving to the characterization of more irregular shapes. As a nonspecialist in this field, I'm surprised that this problem seems to be unresolved in imageJ, esp. by image recognition and computer vision specialists.