Mathematical morphology has been widely used for many applications in image processing and analysis. Most image processing architectures adapted to morphological operations use structuring elements of a limited size. Therefore, difficulties arise when we deal with a large-sized structuring element. In this paper, we present algorithms for the decomposition of arbitrary gray-scale structuring elements into combined dilations or maximum operators of smaller structuring components. Our method does not need to perform additional pre-processes, such as checking the type of structuring elements and the decomposition rules. Furthermore, it is suited for a parallel pipelined architecture.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
- Image processing
- Mathematical morphology
- Structuring element