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Filtering Non-Significant Quench Points Using Collision Impact in Grassfire Propagation
Book chapter   Peer reviewed

Filtering Non-Significant Quench Points Using Collision Impact in Grassfire Propagation

Dakai Jin, Cheng Chen and Punam K Saha
Image Analysis and Processing — ICIAP 2015, pp.432-443
Lecture Notes in Computer Science, Springer International Publishing
08/21/2015
DOI: 10.1007/978-3-319-23231-7_39

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Abstract

The skeleton of an object is defined as the set of quench points formed during Blum’s grassfire transformation. Due to high sensitivity of quench points with small changes in the object boundary and the membership function (for fuzzy objects), often, a large number of redundant quench points is formed. Many of these quench points are caused by peripheral protrusions and dents and do not associate themselves with core shape features of the object. Here, we present a significance measure of quench points using the collision impact of fire-fronts and explore its role in filtering noisy quench points. The performance of the method is examined on three-dimensional shapes at different levels of noise and fuzziness, and compared with previous methods. The results have demonstrated that collision impact together with appropriate filtering kernels eliminate most of the noisy quench voxels while preserving those associated with core shape features of the object
Fire Front Fuzzy Object Maximal Ball Membership Function Skeletonization Algorithm

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