Knowledge Reuse Mechanisms for Categorizing Related Image Sets

Abstract

. This chapter introduces the concept of classier knowledge reuse as a means of exploiting domain knowledge taken from old, previously created, relevant classiers to assist in a new classication task. Knowledge reuse helps in constructing better generalizing classiers given few training examples and for evaluating images for search in an image database. In particular, we discuss a knowledge reuse framework in which a supra-classier improves the performance of the target classi er using information from existing support classiers. Soft computing methods can be used for all three types of classiers involved. We explore supra-classier design issues and introduce several types of supra-classiers, comparing their relative strengths and weaknesses. Empirical examples on real world image data sets are used to demonstrate the eectiveness of the supra-classier framework for classi- cation and retrieval/search in image databases. Keywords: knowledge reuse, image classication, image database, curse of dimensionality, soft classiers