Sg. Tzafestas et Sn. Raptis, Image segmentation via iterative fuzzy clustering based on local space-frequency multi-feature coherence criteria, J INTEL ROB, 28(1-2), 2000, pp. 21-37
Fuzzy set theory has recently attracted much attention in the field of imag
e classification, image understanding and image processing. One of the majo
r topics in fuzzy image processing is the image classification problem. Thi
s paper presents a fast and accurate iterative fuzzy clustering (I.F.C.) me
thod dynamically adapted to the classification process. This is used for hi
gh performance fuzzy segmentation which forms the basis for reliable image
understanding. The proposed fuzzy segmentation scheme examines the image co
nnectivity in the space and frequency domains. The detected fuzzy features
are combined via a block synthesis and local correlation algorithmic proced
ure. Some results showing that the performance of the proposed I.F.C./clust
ering method is superior from that of the standard fuzzy c-means method are
provided.