An Active Contour Based Algorithm for Micro-scale Surface Feature Extraction

Surface feature is the one of the most important factors affecting the functionality and
reliability of micro scale patterned surfaces. For micro scale patterned surface
characterization, it’s important to extract the surface feature effectively and accurately.
The active contours, known as “snakes”, have been successfully used to segment, match
and track the objects of interest. The active contours are wildly implicated in facial
boundary detection, medical image processing, motion correction, etc. In this paper,
surface feature extraction techniques based on active contours have been investigated.
Greedy active contour models and geometric active contour (GAC) models have been
presented. Also, a group of examples has been selected here to demonstrate the
feasibility and applicability of the surface pattern extraction techniques based on active
contours. At last, experimental results will be given and discussed.