Conclusions

• A method for automatic generation of feature recognition rules that is applicable in different application domains is proposed.
• Application of inductive learning techniques
• Coding of features at two levels of abstraction.
• Utilisation of inductive learning techniques for AFR has several advantages:
• Formal mechanism for rule definition + consistency of the generated rule sets
• The development of AFR systems for different application domains requires only representative training sets to be formed for each of them.
• Generalisation capabilities of inductive learning techniques → AFR systems could recognise features that are not present in the training sets.
• The knowledge base of such systems could be extended easily to cover new or user-defined features.