Skeletonization : An Electrostatic Field - Based Approach 1

Skeleton representation of an object is a powerful shape descriptor that captures both boundary and region information of the object. The skeleton of a shape is a representation composed of idealized thin lines that preserve the connectivity or topology of the original shape. Although the literature contains a large number of skeletonization algorithms, many open problems remain. In this paper, we present a new skeletonization approach that relies on the Electrostatic Field Theory (EFT). Many problems associated with existing skeletonization algorithms are solved using the proposed approach. In particular, connectivity, thinness, and other desirable features of a skeleton are guaranteed. It also captures notions of corner detection, multiple scale, thinning, and skeletonization all within one uniied framework. The performance of the proposed EFT-based algorithm is studied extensively. Using the Haus-dorf distance measure, the noise sensitivity of the algorithm is compared to two existing skele-tonization techniques. The experimental results are encouraging. 3 To whom correspondence should be addressed. Grigorishin and Yang would like to dedicate this paper in memory of Abdel-Hamid.