Unsupervised segmentation of texture images using feature selection

Abstract

Highly precise segmentation of texture images is a technique which is indispensable in image understanding and image recognition. This paper proposes a method which represents the features of the texture image by using the wavelet transform, the nonlinear transformation, and a Gaussian filter, which are used in time–frequency analysis. A highly precise segmentation procedure for texture images is presented in which a feature suited to segmentation is selected from among a number of features. The usefulness of the proposed method is demonstrated through experiments using artificial data, and a result for a natural image is presented as an application to a real problem. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 88(9): 58–66, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20208