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Detection of Texture and Isolated Features Using Alternating Morphological Filters

  • Igor Zingman
  • Dietmar Saupe
  • Karsten Lambers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7883)

Abstract

Recently, we introduced a morphological texture contrast (MTC) operator that allows detection of textural and non-texture regions in images. In this paper we provide comparison of the MTC with other available techniques. 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. 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 for extraction of isolated objects such as individual trees or buildings that should be distinguished from forests or urban centers. We furthermore provide an example of how this operator can be used for detection of isolated linear structures. We also derive an extended version of the MFC that works with vector-valued images.

Keywords

Local Binary Pattern Texture Region Texture Detection Texture Area Signal Inversion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Igor Zingman
    • 1
  • Dietmar Saupe
    • 1
  • Karsten Lambers
    • 2
  1. 1.Department of Computer and Information ScienceUniversity of KonstanzGermany
  2. 2.Institute of Archaeology, Heritage Sciences and Art HistoryUniversity of BambergGermany

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