Abstract
Mathematical morphology has been developed recently for many applications in image processing and analysis. Most image processing architectures adapted to morphological operations use structuring elements of limited size. Implementation difficulties arise when an algorithm requires the use of a large size structuring element. In this paper we present techniques for decomposing big grayscale morphological structuring elements into combined structures of segmented small components. According to mathematical morphology properties, such decomposition allows us to equate morphological operations on big structuring elements with operations on decomposed small structuring components. The decomposition is suitable for parallel pipelined architecture. This technique will allow full freedom for users to design any kind and any size of gray-scale morphological structuring element.
Original language | English (US) |
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Pages (from-to) | 195-203 |
Number of pages | 9 |
Journal | Pattern Recognition |
Volume | 24 |
Issue number | 3 |
DOIs | |
State | Published - 1991 |
All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
Keywords
- Decomposition
- Distance transformation
- Gray-scale morphology
- Image processing
- Mathematical morphology
- Thresholding