This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Min-Max Medial Axis Transformation
February 1981 (vol. 3 no. 2)
pp. 208-210
Shmuel Peleg, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742.
Azriel Rosenfeld, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742.
Blum's medial axis transformation (MAT) of the set S of 1's in a binary picture can be defined by an iterative shrinking and reexpanding process which detects ``corners'' on the contours of constant distance from S¿, and thereby yields a ``skeleton'' of S. For unsegmented (gray level) pictures, one can use an analogous definition, in which local MIN and MAX operations play the roles of shrinking and expanding, to compute a ``MMMAT value'' at each point of the picture. The set of points having high values defines a good ``skeleton'' for the set of high-gray level points in the given picture.
Citation:
Shmuel Peleg, Azriel Rosenfeld, "A Min-Max Medial Axis Transformation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 3, no. 2, pp. 208-210, Feb. 1981, doi:10.1109/TPAMI.1981.4767082
Usage of this product signifies your acceptance of the Terms of Use.