An application of the multiedit-condensing technique to the reference selection problem in a print recognition system

摘要

In this paper we address the elusive problem of selecting references (templates) for minimum distance classification when the number of pattern classes is very large. We argue that the multiedit/condensing technique offers an automatic solution to this problem which avoids the proliferation of references without impairing the recognition performance. The effectiveness of the approach is demonstrated by experimental results in a print recognition context. Suggestions are made about ways of circumventing problems of computational complexity.