A STATISTICAL COMBINED CLASSIFIER AND ITS APPLICATION TO REGION AND IMAGE CLASSIFICATION
Steven J. Simske · 2005
archiving, zoning analysis, image classification, classifier, binary classification, normal, combined classifiers A new method for combining classifiers is introduced for two problem types. (1) Archiving and re-purposing are automated using zoning analysis that performs segmentation (region boundary definition), classification (region typing) and bit-depth determination. For performance throughput reasons, zoning analysis is often performed on a low-resolution (e.g. 50-100 ppi) representation of the document. At these resolutions, heuristic metrics for classification are required. Reported here are metrics for distinguishing photos and color drawings, and a novel classification technique based solely on the statistics of each heuristic metric. The statistical technique allows ready combination of multiple binary classifiers, and provides a lower classification error than