We have developed a robust method for image segmentation based on a local multiscale texture description. We first apply a set of 4 by 4 complex Gabor filters, plus a low-pass residual (LPR), producing a log-polar sampling of the frequency domain. Contrary to other analysis methods, our Gabor scheme produces a visually complete multipurpose representation of the image, so that it can also be applied to coding, synthesis, etc. Our sixteen texture features consist of local contrast descriptors, obtained by dividing the modulus of the response of the complex Gabor filter by that of the LPR at each location. Contrast descriptors are basically independent of slow variations in intensity, while increasing the robustness and invariance of the representation. Before applying the segmentation algorithm, we equalize the number of samples of the four layers in the resulting pyramid of local contrast descriptors. This method has been applied to segmentation of electron microscopy images, obtaining very good results in this real case, where robustness is a basic requirement, because intensity, textures and other factors are not completely homogeneous.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.