Color image segmentation using fuzzy C-means and eigenspace projections

In this paper, we propose two eigen-based fuzzy C-means (FCM) clustering algorithms to accurately segment the desired images, which have the same color as the pre-selected pixels. From the selected color pixels, we can first divide the color space into principal and residual eigenspaces. Combined eigenspace transform and the FCM method, we can effectively achieve color image segmentation. The separate eigenspace FCM (SEFCM) algorithm independently applies the FCM method to principal and residual projections to obtain two intermediate segmented images and combines them by logically selecting their common pixels. Jointly considering principal and residual eigenspace projections, we then suggest the coupled eigen-based FCM (CEFCM) algorithm by using an eigen-based membership function in clustering procedure. Simulations show that the proposed SEFCM and CEFCM algorithms can successfully segment the desired color image with substantial accuracy.