Parametric characterization of the form of the human pupil from blurred noisy images.
The fluctuation of the human pupil is an important parameter in order to make non-invasive diagnosis of many different diseases and in several clinical applications. The relevant measurement device, the pupillometer, consists in a CCD camera, which shoots the pupil. We suppose that the measured image is blurred by a Gaussian kernel and corrupted by an additive white noise; moreover an elliptic shape for the pupil is assumed. We here present the extension of a multiscale approach for edge detection to identify some parameters of the pupil: the location of its centre, the length of the semi-axes and the orientation of the corresponding ellipse. The chosen method requires knowledge about the degradation parameters of the assumed model; so we first present a simple but efficient method to determine such quantities for the measured image. Then we apply the edge detection procedure to identify points close to the pupil edge, within a chosen probability. Finally we find the optimal ellipse fitting a suitable subset of the previously detected edge points. Results are presented, with comparisons to other approaches for edge finding.
Iacoviello
Daniela
D
Department of Computer and Systems Science Antonio Ruberti, University of Rome La Sapienza, Via Eudossiana 18, 00184 Rome, Italy. iacoviel@dis.uniroma1.it
Lucchetti
Matteo
M
D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007498:Iris / Q000033:anatomy & histology*; D008953:Models, Anatomic; D010781:Photography; D011680:Pupil; D012984:Software