General-Purpose Localization of Textured Image Regions

We suggest a working definition of texture: Texture is stuff that is more compactly represented by its statistics than by specifying the configuration of its parts. This definition suggests that to fmd texture we look for outliers to the local statistics, and label as texture the regions with no outliers. We present a method, based upon this idea, for labeling points in natural scenes as belonging to texture regions, while simultaneously allowing us to label lowlevel, bottom-up cues for visual attention. This method is based upon recent psychophysics results on processing of texture and popout. 1 WHAT IS TEXTURE, AND WHY DO WE WANT TO FIND IT? In a number of problems in computer VlSlon and image processing, one must distinguish between image regions that correspond to objects and those which correspond to texture, and perform different processing depending upon the type of region. Current computer vision algorithms assume one magically knows this region labeling. But what is texture? We have the notion that texture involves a pattern that is somehow homogeneous, or in which signal changes are "too complex" to describe, so that aggregate properties must be used instead (Saund, 1998). There is by no means a firm division between texture and objects; rather, the characterization often depends upon the scale of interest (Saund, 1998). • Email: [email protected]