Image segmentation is the first step in object-oriented image analysis. Segmentation in gray scale images results in ill-defined object boundaries. This uncertainty can be handled by describing different objects as rough sets. This paper presents an algorithm for image object extraction in the context of rough set theory. Based on the concept of image granules a measure called ‘‘Mean Roughness Measure” is defined by which we can compute an optimal threshold for image segmentation.