Abstract
Mathematical morphology which is based on geometric shape, provides an approach to the processing and analysis of digital images. Several widely-used geometric-shaped structuring elements can be used to explore the shape characteristics of an object. A unified technique is presented to simplify the decomposition of various types of big geometric-shaped structuring elements into dilations of smaller structuring components by the use of a mathematical transformation. Hence, the desired morphological erosion and dilation are equivalent to a simple inverse transformation over the result of operations on the transformed decomposable structuring elements. A strategy is also presented to decompose a large cyclic cosine structuring element. The technique of decomposing a two-dimensional (2D) convex structuring element into one-dimensional (1D) ones is also developed.
Original language | English (US) |
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Pages (from-to) | 1097-1106 |
Number of pages | 10 |
Journal | Pattern Recognition |
Volume | 25 |
Issue number | 10 |
DOIs | |
State | Published - Oct 1992 |
All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
Keywords
- Decomposition
- Distance transformation
- Geometry
- Mathematical morphology
- Structuring element