A FCM and SURF based algorithm for segmentation of multispectral face images

Ahmed Ben Said, Sebti Foufou, Mongi Abidi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a novel clustering algorithm based on Fuzzy C-Means (FCM) and Speeded-Up Robust Feature (SURF) for multispectral image segmentation. In the experiments, color images and multispectral images from IRIS Lab data base, which consists of face images taken along the visible spectrum, have been used to illustrate the performances of the proposed algorithm and to compare its outputs with other algorithms. Results demonstrate that the proposed method outperforms other clustering methods in segmenting color images as well as multispectral images.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2013
Pages65-70
Number of pages6
DOIs
Publication statusPublished - Dec 1 2013
Event2013 9th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2013 - Kyoto, Japan
Duration: Dec 2 2013Dec 5 2013

Other

Other2013 9th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2013
CountryJapan
CityKyoto
Period12/2/1312/5/13

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Keywords

  • Clustering
  • Multispectral image
  • Segmentation
  • SURF

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

Cite this

Said, A. B., Foufou, S., & Abidi, M. (2013). A FCM and SURF based algorithm for segmentation of multispectral face images. In Proceedings - 2013 International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2013 (pp. 65-70). [6727171] https://doi.org/10.1109/SITIS.2013.22