Complete gradient clustering algorithm for features analysis of X-ray images / Małgorzata Charytanowicz, Jerzy Niewczas, Piotr Kulczycki, Piotr A. Kowalski, Szymon Łukasik, Sławomir Żak // W: Information ... więcej

Complete gradient clustering algorithm for features analysis of X-ray images / Małgorzata Charytanowicz, Jerzy Niewczas, Piotr Kulczycki, Piotr A. Kowalski, Szymon Łukasik, Sławomir Żak // W: Information technologies in biomedicine. Vol. 2 / eds. Ewa Piȩtka, Jacek Kawa. - Berlin ; Heidelberg : Springer-Verlag, 2010. - (Advances in Intelligent and Soft Computing, ISSN 1867-5662 ; 69). - S. 15-24 : il. - Bibliogr. 16 poz., Abstr. - doi: 10.1007/978-3-642-13105-9_2. - ISBN 978-3-642-13104-2

Methods based on kernel density estimation have been successfully applied for various data mining tasks. Their natural interpretation together with suitable properties make them an attractive tool among ... więcej

Methods based on kernel density estimation have been successfully applied for various data mining tasks. Their natural interpretation together with suitable properties make them an attractive tool among others in clustering problems. In this paper, the Complete Gradient Clustering Algorithm has been used to investigate a real data set of grains. The wheat varieties, Kama, Rosa and Canadian, characterized by measurements of main grain geometric features obtained by X-ray technique, have been analyzed. The proposed algorithm is expected to be an effective tool for recognizing wheat varieties. A comparison between the clustering results obtained from this method and the classical k-means clustering algorithm shows positive practical features of the Complete Gradient Clustering Algorithm.