Using CBR Learning for the Low-Level and High-Level Unit of an Image Interpretation System [chapter]

Petra Perner
1999 International Conference on Advances in Pattern Recognition  
The existing image interpretation systems lack robustness and accuracy. They cannot adapt to changing environmental conditions and to new objects. The application of machine learning to image interpretation is the next logical step. Our proposed approach aims at the development of dedicated machine learning techniques at all levels of image interpretation in a systematic fashion. In the paper we propose a system, which uses Case-Based Reasoning (CBR) to optimize image segmentation at the low
more » ... el according to changing image acquisition conditions and image quality. The intermediate-level unit extracts the case representation used by the highlevel unit for further processing. At the high level, CBR is employed to dynamically adapt image interpretation.
doi:10.1007/978-1-4471-0833-7_5 fatcat:fttoup6mqvbwdmzgnba7xzxudm