A segmentation method for images compressed by fuzzy transforms
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 d...
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| Vydáno v: | Fuzzy sets and systems Ročník 161; číslo 1; s. 56 - 74 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
2010
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| ISSN: | 0165-0114, 1872-6801 |
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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). |
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| AbstractList | 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). |
| Author | Loia, Vincenzo Sessa, Salvatore Di Martino, Ferdinando |
| Author_xml | – sequence: 1 givenname: Ferdinando surname: Di Martino fullname: Di Martino, Ferdinando email: fdimarti@unina.it organization: Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Via Ponte Don Melillo, 84084 Fisciano, Salerno, Italy – sequence: 2 givenname: Vincenzo surname: Loia fullname: Loia, Vincenzo email: loia@unisa.it organization: Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Via Ponte Don Melillo, 84084 Fisciano, Salerno, Italy – sequence: 3 givenname: Salvatore surname: Sessa fullname: Sessa, Salvatore email: sessa@unina.it, salvatore.sessa@alice.it organization: Università degli Studi di Napoli Federico II, Dipartimento di Costruzioni e Metodi Matematici in Architettura, Via Monteoliveto 3, 80134 Napoli, Italy |
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| Keywords | Image segmentation Lukasiewicz t-norm PSNR FGFCM Similarity measure Fuzzy relation PCAES Fuzzy transform |
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| Title | A segmentation method for images compressed by fuzzy transforms |
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