Generation of the Euclidean Skeleton from the Vector Distance Map by a Bisector Decision Rule

The Euclidean skeleton is essential for general shape representation. This paper provides an e cient method to extract a well-connected Euclidean skeleton by a neighbor bisector decision NBD rule on a vector distance map. The shortest vector which generates a pixel's distance is stored when calculating the distance map. A skeletal pixel is extracted by checking the vectors of the pixel and its 8 neighbors. This method succeeds in generating a well-connected Euclidean skeleton without any linking algorithm. A theoretical analysis and many experiments with images of di erent sizes also shows the NBD rule works excellent. The average complexity of the method with the NBD rule algorithm and the vector distance transform algorithm is linear in the number of the pixels.

• Type: Conference
• Year: 1998
• Where: CVPR
• Authors: Hong Li, Albert M. Vossepoel
• Keywords: Computer Vision, CVPR 1998, Decision Nbd Rule, Distance Transform Algorithm, NBD Rule Algorithm, Vector Distance Map, Well-connected Euclidean Skeleton