Fuzzy clustering of digital images by exploiting densitometric and topological information

Topological features are very seldom exploited in image processing, also due to the complexity of their extraction. When topological features are used, densitometric information are usually not considered at the same time. The simultaneous exploitation of both kinds of features, as proposed in this paper, allows a more appropriate automatic processing of digital images. A novel image segmentation approach is presented (based on fuzzy clustering) that exploits topological and densitometric image features. The novelty of such image segmentation consists mainly in using easy and fast computation methods to improve the handling of any digital image, whenever automatic segmentation or data reduction processing is required.