Abstract
In this paper a fuzzy method for pixel classification is proposed. It is one of the most important results of the development of an inspection system for a silk-screen printing process. The classification algorithm is applied to a reference image in the initial step of the printing process in order to obtain regions which are to be checked by applying different criteria. Tight limitations in terms of computation speed have necessitated very specific, efficient methods which operate locally. These methods are motivated and presented in detail in the following. Furthermore, the optimization of the parameters of the classification system with genetic algorithms is discussed. Finally, the genetic approach is compared with other probilistic optimization methods.
| Original language | English |
|---|---|
| Title of host publication | Proc. IFSA'97 |
| Number of pages | 6 |
| Volume | 4 |
| Publication status | Published - Jun 1997 |
Fields of science
- 101 Mathematics
- 101004 Biomathematics
- 101027 Dynamical systems
- 101013 Mathematical logic
- 101028 Mathematical modelling
- 101014 Numerical mathematics
- 101020 Technical mathematics
- 101024 Probability theory
- 102001 Artificial intelligence
- 102003 Image processing
- 102009 Computer simulation
- 102019 Machine learning
- 102023 Supercomputing
- 202027 Mechatronics
- 206001 Biomedical engineering
- 206003 Medical physics
- 102035 Data science