Title :
Image Analysis Using Mathematical Morphology
Author :
Haralick, Robert M. ; Sternberg, Stanley R. ; Zhuang, Xinhua
Author_Institution :
Department of Electrical Engineering, University of Washington, Seattle, WA 98195.
fDate :
7/1/1987 12:00:00 AM
Abstract :
For the purposes of object or defect identification required in industrial vision applications, the operations of mathematical morphology are more useful than the convolution operations employed in signal processing because the morphological operators relate directly to shape. The tutorial provided in this paper reviews both binary morphology and gray scale morphology, covering the operations of dilation, erosion, opening, and closing and their relations. Examples are given for each morphological concept and explanations are given for many of their interrelationships.
Keywords :
Computer architecture; Convolution; Image analysis; Image texture analysis; Logic arrays; Machine vision; Morphological operations; Morphology; Robotic assembly; Shape; Closing; dilation; erosion; filtering; image analysis; morphology; opening; shape analysis;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1987.4767941