Summary: IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 9, NO. 4, APRIL 2000 623
Scale Space Classification Using Area Morphology
Scott T. Acton, Senior Member, IEEE, and Dipti Prasad Mukherjee
Abstract--We explore the application of area morphology to
image classification. From the input image, a scale space is created
by successive application of an area morphology operator. The
pixels within the scale space corresponding to the same image
location form a scale space vector. A scale space vector therefore
contains the intensity of a particular pixel for a given set of scales,
determined in this approach by image granulometry. Using the
standard -means algorithm or the fuzzy -means algorithm,
the image pixels can be classified by clustering the associated
scale space vectors. The scale space classifier presented here is
rooted in the novel area open­close and area close­open scale
spaces. Unlike other scale generating filters, the area operators
affect the image by removing connected components within the
image level sets that do not satisfy the minimum area criterion. To
show that the area open­close and area close­open scale spaces
provide an effective multiscale structure for image classification,
we demonstrate the fidelity, causality, and edge localization prop-

Source: Acton, Scott - Department of Electrical and Computer Engineering, University of Virginia

Collections: Computer Technologies and Information Sciences