Mathematical morphology has been becoming an increasingly important and often-used technique in image processing and machine vision applications during recent decades. Nevertheless, the iterations of morphological operations exist a bottleneck in implementation on a pipelined parallel architecture. The objectives of this project are to propose a set of new morphological operators, called back-propagation morphology, which is different from the traditionally defined morphology for solving time-consuming iteration problems, and to develop its underlying theorems, algorithms and architectures for various vision applications. First-stage experiments show that the back-propagation morphology has the advantages of deriving a root of a signal which only requires two scans without numerous iterations and being suited for parallel architectures. It is anticipated that the proposed research program will lead to fundamental advances in the theoretical understanding of the new back-propagation morphological operations. The algorithms and architectures developed and the research findings produced by the project will also have substantial utility for industry in advancing machine vision inspection and recognition technologies.
|Effective start/end date||7/1/91 → 12/31/93|
- National Science Foundation: $63,685.00