Title :
A FCM and SURF Based Algorithm for Segmentation of Multispectral Face Images
Author :
Ben Said, Ahmed ; Foufou, Sebti ; Abidi, Mouadh
Author_Institution :
CSE Dept., Qatar Univ., Doha, Qatar
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.
Keywords :
feature extraction; image colour analysis; image segmentation; pattern clustering; FCM based algorithm; IRIS Lab database; SURF based algorithm; clustering methods; color images; fuzzy c-means; image segmentation; multispectral face image; speeded-up robust feature; visible spectrum; Clustering algorithms; Color; Face; Feature extraction; Image segmentation; Indexes; Principal component analysis; SURF; clustering; multispectral image; segmentation;
Conference_Titel :
Signal-Image Technology & Internet-Based Systems (SITIS), 2013 International Conference on
Conference_Location :
Kyoto
DOI :
10.1109/SITIS.2013.22