Title :
A segmentation method based on fuzzy topology and clustering
Author :
Mari, M. ; Dellepiane, S.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Abstract :
In addition to clustering, a fuzzy approach to image segmentation is proposed in this work also for the handling of spatial information of topological type. Topological information is taken into account, extending the fuzzy connectivity, to define a segmentation method of grey level images. The main innovative aspects of the proposed method consist in the automatic processing of real images, without using any parameter and fixed threshold, and in the simplicity and speed of the computation, realised through simple fuzzy operators and a noniterative growing mechanism. Quantitative evaluation of preliminary results, obtained on real images from various application domains, proves the feasibility of the method
Keywords :
fuzzy set theory; image recognition; image segmentation; topology; clustering; fuzzy connectivity; fuzzy operators; fuzzy topology; grey level images; image segmentation; noniterative growing mechanism; quantitative evaluation; Circuit topology; Clustering algorithms; Image analysis; Image segmentation; Information analysis; Partitioning algorithms; Pattern analysis; Pattern recognition; Robustness; Uncertainty;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.546887
