Color object segmentation with eigen-based fuzzy C-means

In this paper, we propose an eigen-based fuzzy C-means (FCM) method for color object segmentation. After sampling a few color samples, we can form the sampled covariance matrix and its related eigenvectors of the desired color space. Then, we transform the original color space into signal and noise planes of the desired color. Followed the transformation, the proposed eigen-based FCM algorithm is finally applied to the signal and noise subspaces individually. After few iterated classification processes, the desired color objects can be easily identified without using any threshold procedure. Inspecting the segmented results, the desired color objects without any pre- and post-processes can be extracted easily and robustly.