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Journal of Applied Nonlinear Dynamics 6(2) (2017) 181--191 | DOI:10.5890/JAND.2017.06.005

Tiago Bento $^{1}$,$^{2}$, Duarte Valério$^{1}$, Pedro Teodoro$^{3}$, Jorge Martins$^{1}$

$^{1}$ IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

$^{2}$ Deloitte Portugal, Portugal

$^{3}$ Escola Superior Náutica Infante D. Henrique, Paço d’Arcos, Portugal

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Abstract

To perform a robot-assisted surgery of a prosthesis implantation on a patient’s femur, we may need to get the femoral head-neck orientation for the application. We can extract that information from Computed Tomography scans, using image processing. In image processing, edge detection often makes use of integer-order differentiation operators (e.g. Canny and LoG operators). This paper shows that introducing non-integer (fractional) differentiation to edge detectors (Fractional Canny, Fractional LoG, Fractional Derivative operators) can improve automatic edge detection results.

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