Computer Recognition Systems pp 387-394
Image Decomposition by Grade Analysis - an Illustration
- Cite this paper as:
- Grzegorek M. (2005) Image Decomposition by Grade Analysis - an Illustration. In: Kurzyński M., Puchała E., Woźniak M., żołnierek A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg
Two test images are decomposed into sequences of ten ordered images which result from a clustering of pixels. The first image is supposed to contain pixels belonging to edge, the tenth image — pixels belonging to region interior. The remaining images gradually change from edge related to interior related. The clustering is provided by the so called Grade Correspondence — Cluster Analysis (GCCA), described in lastly published book on grade models and methods for data analysis. The GCCA is applied to the data matrices formed by a set of 12 variables which include gradient module, gray level, and ten variables describing the nearest neighborhood of each pixel according to the increasing level of module diffierentiation. Data matrices are visualized in form of the so called “ordered overrepresentation maps” and “grade stripcharts”.
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