- Title
- A genetic algorithm to obtain optimum parameters for a halcon vision system
- Creator
- Fulton, Dale Meares
- Subject
- Genetic algorithms
- Subject
- Artificial intelligence
- Subject
- Automation
- Subject
- User interfaces (Computer systems)
- Date Issued
- 2017
- Date
- 2017
- Type
- Thesis
- Type
- Masters
- Type
- MEng
- Identifier
- http://hdl.handle.net/10948/29751
- Identifier
- vital:30774
- Description
- This report discusses the optimisation of a HALCON vision system using artificial intelligence, specifically a genetic algorithm. Within industrial applications, vision systems are often used for automated part inspection and quality control. A number of vision system parameters are to be selected when setting up a vision system. Since each vision system application differs, there is no specific set of optimal parameters. Parameters are selected during installation using a trial and error method. As a result, there is a need for an automated process for obtaining suitable vision system parameters. Within this report, research was conducted on both vision systems, genetic algorithms and integration of the two. A physical vision system was designed and developed utilising HALCON vision software. A genetic algorithm was then developed and integrated with the vision system. After integration, experimental testing was performed on the genetic algorithm in order to determine the ideal genetic algorithm control parameters which yield ideal genetic algorithm performance. Once the ideal genetic algorithm was obtained, the genetic algorithm was applied to the vision system in order to obtain optimal vision system parameters. Results showed that applying the genetic algorithm to the vision system optimised the vision system performance well.
- Format
- v, 189 leaves
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Engineering, the Built Environment and Information Technology
- Language
- English
- Rights
- Nelson Mandela University
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | FultonMasters.pdf | 23 MB | Adobe Acrobat PDF | View Details Download |