A segmentation method for images compressed by fuzzy transforms

Authors:
Ferdinando Di Martino;Vincenzo Loia;Salvatore Sessa
Affiliations:
Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Via Ponte Don Melillo, 84084 Fisciano, Salerno, Italy and Università degli Studi di Napoli Federico II, Dipar ...;Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Via Ponte Don Melillo, 84084 Fisciano, Salerno, Italy;Università degli Studi di Napoli Federico II, Dipartimento di Costruzioni e Metodi Matematici in Architettura, Via Monteoliveto 3, 80134 Napoli, Italy
Venue:
Fuzzy Sets and Systems
Year:
2010

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Abstract

In this paper we describe a segmentation method applied to images which are compressed by using Fuzzy Transforms. The segmentation of the images is realized via the FGFCM (Fast Generalized Fuzzy C-Means) clustering algorithm, which is robust to noise and outliers. The optimal number of clusters is determined via the PCAES (Partition Coefficient And Exponential Separation) validity index. We use a similarity measure defined via Lukasiewicz t-norm for comparison between the original image and the reconstructed images. The best results are obtained if this similarity measure overcomes a threshold value, experimentally determined from the analysis of the trend of it with respect to the PSNR (Peak Signal to Noise Ratio).