Nonlinear optimisation method for image segmentation and noise reduction using geometrical intrinsic properties

Authors:
S. Mahmoodi;B. S. Sharif
Affiliations:
Psychology Department, School of Biology, Henry Wellcome Building, Newcastle University, Newcastle upon Tyne, NE2 4HH;School of Electrical, Electronic and Computer Engineering, Merz Court, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
Venue:
Image and Vision Computing
Year:
2006

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Abstract

This paper considers the optimisation of a nonlinear functional for image segmentation and noise reduction. Equations optimising this functional are derived and employed to detect edges using geometrical intrinsic properties such as metric and Riemann curvature tensor of a smooth differentiable surface approximating the original image. Images are then smoothed using a Helmholtz type partial differential equation. The proposed approach is shown to be very efficient and robust in the presence of noise, and the reported results demonstrate better performance than the conventional derivative based edge detectors.