A morphological approach for distinguishing texture and individual features in images

Abstract

We present a morphological texture contrast (MTC) operator that allows detection of textural and nontexture regions in images. We show that in contrast to other approaches, the MTC discriminates between texture details and isolated features and does not extend borders of texture regions. A comparison with other methods used for texture detection is provided. Using the ideas underlying the MTC operator, we develop a complementary operator called morphological feature contrast (MFC) that allows extraction of isolated features while not being confused by texture details. We illustrate an application of the MFC operator to extraction of isolated objects such as individual trees or buildings that should be distinguished from forests or urban centers. We also propose an MFC based detector of isolated linear features and compare it with an alternative approach used for detection of edges and lines in cluttered scenes. We furthermore derive an extended version of the MFC that can be directly applied to vector-valued images.