Towards an efficient and robust foot classification from pedobarographic images

Abstract

This paper presents a new computational framework for automatic foot classification from digital plantar pressure images. It classifies the foot as left or right and simultaneously calculates two well-known footprint indices: the Cavanagh's arch index (AI) and the modified AI. The accuracy of the framework was evaluated using a set of plantar pressure images from two common pedobarographic devices. The results were outstanding, as all feet under analysis were correctly classified as left or right and no significant differences were observed between the footprint indices calculated using the computational solution and the traditional manual method. The robustness of the proposed framework to arbitrary foot orientations and to the acquisition device was also tested and confirmed.

Keywords:

• biomechanics
• computational methods
• image analysis
• image alignment
• plantar pressure images
• footprint indices

Acknowledgements

This work was partially done under the scope of the following research projects ‘Methodologies to Analyse Organs from Complex Medical Images – Applications to the Female Pelvic Cavity’, ‘Cardiovascular Imaging Modeling and Simulation – SIMCARD’ and ‘Aberrant Crypt Foci and Human Colorectal Polyps: Mathematical Modelling and Endoscopic Image Processing’, with the references PTDC/EEA-CRO/103320/2008, UTAustin/CA/00 47/2008 and UTAustin/MAT/0009/2008, respectively, and financially supported by FCT – Fundação para a Ciência e a Tecnologia in Portugal.

The first author would like to thank Fundação Calouste Gulbenkian, in Portugal, for his PhD grant.