Model-Based On-Line Fault Detection and Image Classification
Sprache des Vortragstitels:
In many machine vision applications, such as inspection
tasks for quality control, an automatic system tries to reproduce human
cognitive abilities. The most efficient and flexible way to achieve this, is
to learn the task from a human expert. This training process involves object recognition methods, adaptive feature extraction algorithms and
evolving classifiers. A lot of research has been done on each of these topics,
however, simply plugging all of these methods together does not necessarily
lead to a working machine vision system.
In this talk, a generic self-adaptive image classification framework is presented, focussing on integration
issues and on topics that are specific to quality control applications.