@ARTICLE{BackesCB09b,
	author = {Andre Ricardo Backes and Dalcimar Casanova and Odemir Martinez Bruno},
	title = {A complex network-based approach for boundary shape analysis},
	journal = {Pattern Recognition},
	volume = {42},
	number = {1},
	pages = {54-67},
	year = {2009},
	abstract = {This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degrdoi and joint degrdoi measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has an efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on thrdoi image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, curvature, Zernike moments and multiscale fractal dimension).},
	keywords = {Shape analysis; Shape recognition; Complex network; Small-world model},
	doi = {10.1016/j.patcog.2008.07.006}
}