期刊
PATTERN RECOGNITION
卷 37, 期 5, 页码 901-915出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2003.09.009
关键词
mathematical morphology; scale space; top-hat transform; bottom-hat transform; connected operators; pattern classification; decision trees; diatom images; Brodatz textures
In this paper we present a multi-scale method based on mathematical morphology which can successfully be used in pattern classification tasks. A connected operator similar to the morphological hat-transform is defined, and two scale-space representations are built. The most important features are extracted from the scale spaces by unsupervised cluster analysis, and the resulting pattern vectors provide the input of a decision tree classifier. We report classification results obtained using contour features, texture features, and a combination of these. The method has been tested on two large sets, a database of diatom images and a set of images from the Brodatz texture database. For the diatom images, the method is applied twice, once on the curvature of the outline (contour), and once on the grey-scale image itself. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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