In this paper, we present a new system to segment and label document images into text, images, and background using a modified Fuzzy C-means Algorithm. Each pixel is assigned a feature pattern extracted from the gray level distribution and computed at different scales. The invariant feature pattern is then assigned to a specific region using Fuzzy logic. Our algorithm is formulated by modifying the objective function of the standard fuzzy c-means (FCM) algorithm to allow the labeling of a pixel to be influenced by the labels in its immediate neighborhood. The neighborhood effect acts as a regularizer and biases the solution towards piecewise-homogeneous labelings. Such a regularization is useful in segmenting scans corrupted by scanner noise.