Premium
Registration of plantar pressure images
Author(s) -
Oliveira Francisco P.M.,
Tavares João Manuel R.S.
Publication year - 2011
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.1461
Subject(s) - robustness (evolution) , residual , fourier transform , mean squared error , artificial intelligence , phase correlation , image registration , computer science , cross correlation , mathematics , computer vision , pattern recognition (psychology) , algorithm , fourier analysis , image (mathematics) , short time fourier transform , statistics , mathematical analysis , biochemistry , chemistry , gene
SUMMARY In this work, five computational methodologies to register plantar pressure images are compared: (1) the first methodology is based on matching the external contours of the feet; (2) the second uses the phase correlation technique; (3) the third addresses the direct maximization of cross‐correlation using the Fourier transform; (4) the fourth minimizes the sum of squared differences using the Fourier transform; and (5) the fifth methodology iteratively optimizes an intensity (dis)similarity measure based on Powell's method. The accuracy and robustness of the five methodologies were assessed by using images from three common plantar pressure acquisition devices: a Footscan system, an EMED system, and a light reflection system. Using the residual error as a measure of accuracy, all methodologies revealed to be very accurate even in the presence of noise. The most accurate was the methodology based on the iterative optimization, when the mean squared error was minimized. It achieved a residual error inferior to 0.01 mm and 0.6 mm for non‐noisy and noisy images, respectively. On the other hand, the methodology based on image contour matching was the fastest, but its accuracy was the lowest. Copyright © 2011 John Wiley & Sons, Ltd.